Analysing the Link between Population Diversity, Population Growth, and Income

Analysing the Link between Population Diversity, Population Growth, and Income | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Analysing the Link between Population Diversity, Population Growth, and Income Irfan Aziz Al Firdaus, Cokorda Bagus Ghana Indra Pradana, Catur Sugiyanto This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4115318/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Amidst shifting demographics across many countries, certain stylized facts related to fertility, population, and income have become less universally applicable. This research addresses a significant gap in literature by providing a comprehensive analysis on the relationship between population diversity, population growth, and income growth that incorporate both time-varying and cross-country components. Our study reveals a positive correlation between population diversity and population growth, suggesting that diversity along with migration contribute to population expansion due to strategic interactions among ethnic groups to compete for influences in society, hence fostering pronatalism policies. However, we found a negative association between population diversity and income growth, indicating potential ethnic conflict, rent-seeking behaviour, and other challenges that hinder policy implementation in highly diverse settings. Our findings underline the complex dynamics between these factors, emphasizing the need for further exploration. JEL Classification: J1, O1, Z1 Other Economics Diversity Population Growth Income Figures Figure 1 Figure 2 1. Introduction The world’s population is expected to increase by 2 billion, from 7.7 billion to 9.7 billion, by 2050 and reach a peak close to 11 billion at the end of the century as the world battles with declining fertility rates (United Nations, 2020 ). The global fertility rate is expected to fall from 2.5 in 2019 to 1.9 births per woman by the year 2100 and the global median age is also projected to rise from 31 to 42 in the same period (Cilluffo & Ruiz, 2019 ). The relationship between demographic parameters, such as population and fertility, is a complex and multifaceted topic that has been the subject of much research and debate. Fertility, or the birth of children per woman, is influenced by a wide range of factors, including biological, social, economic, and environmental factors (Bao, 2021 ). At the same time, demographic change which studies how human population changes over time is driven by a combination of fertility rates, mortality rates, age profile of the population, and migration patterns (Pew Research Center, 2015 ; Ranganathan, Swain, & Sumpter, 2015 ). Despite the importance of understanding the impact of diversity on societal dynamics, there is a surprising lack of research specifically examining how the racial and ethnic diversity of a population may influence its growth. This is of great significance as a population with a variety of ethnic groups can result in strategic interactions that promote pronatalism and increase fertility rates, as leaders of these groups encourage policies that boost fertility and population (Papyrakis & Mo, 2014 ). The motivation to further examine this topic also originates from observing Japan with declining population growth and having one of the most homogeneous populations even among advanced economies. Japan’s population has been dwindling mainly due to falling fertility rate, which ranged at 1.3 for the 2019—2021 period, while the ideal replacement fertility rate or the number of children a woman needs to have for the population to sustain itself is 2.1 children for every woman (OECD, 2023 ). At the same time, this population problem may be exacerbated by the fact that Japan is ethnically homogeneous. The Japanese population comprises 97.8% of Japan’s total population making it one of the most ethnically homogeneous country among advanced economies (Statistics Bureau of Japan, 2021 ). Conversely, countries with higher fertility rates, such as India and Indonesia, tend to be more ethnically heterogeneous. Both countries have a fertility rate of 2.03 and 2.17 respectively in 2021 which are still relatively close to the ideal replacement fertility rate while having a large varying ethnicity number (OECD, 2023 ). India alone is a highly diverse country with over 2,000 ethnic groups representing each of the world’s major religions (Statista, 2023 ). The majority of these ethnic groups in India are Indo-Aryan and Dravidian, constituting 72% and 25% of India's total population, respectively, while other ethnic groups account for 3% of the total population (Central Intelligence Agency, 2023 ). Similarly, the Indonesian population is also incredibly diverse, comprising over 1330 ethnic groups, with the two largest being the Javanese, who make up 40.05% of the total population, and the Sundanese, who make up 15.5%, while the proportion of the remaining ethnic groups are less than 5 percent each (Statistics Indonesia, 2015 ). These facts underline the possible connection between a given country’s diversity and its population growth, highlighting the need for further research into potential relationship between the aforementioned issues and how it affects economic outcome. Previous discussion on fertility has ushered in a new era that brings a different demographic implication as some of these initially stylized facts are no longer universally relevant. The first-generation empirical modelling for fertility were made to account for two regularities that has held for many decades across nations and within families in a particular country i.e., a negative relationship between income and fertility as well as a negative relationship between women’s labour force participation and fertility (Doepke, Hannusch, Kindermann, & Tertilt, 2022 ). Such trade-offs relate heavily to the quantity-quality trade-off theory of Becker & Lewis ( 1973 ) that a smaller family size allows for more resources to be allocated to each child which improves the overall child quality within a family given the limited resources available, therefore implying that a decrease in fertility would encourage more human capital investment for every child (Wang & Zhang, 2018 ). Lately, however, such consensus in said quantity-quality trade-offs mentioned beforehand has been undergoing a major shift. Across the high-income world, some evidence of the positive relationship between fertility and income has been observed with shifting key determinants of fertility choice mainly due to changing family policy and social norms, the trend of accommodating fathers, as well as flexible labour markets (Doepke et al., 2022 ). Meanwhile, the topics of racial or ethnic diversity and demographic have also gathered much attention in recent times. By 2050, it is estimated that half of the world’s population growth mostly originates from Asian and African countries such as India, Nigeria, Pakistan, the Democratic Republic of the Congo, Ethiopia, Tanzania, Indonesia, Egypt, and the United States of America (in descending order of growth) (United Nations, 2020 ) with one in four of the total global population having Sub-Saharan Africa origin by that same period (Suzuki, 2019 ). India has overtaken China in terms of population number in 2023, becoming the world’s most populous country, and both countries face divergent demographic future with China suffering from declining populations due to falling fertility rates and India’s population is still set to continue growing (United Nations, 2019 , 2023 ). Thus, it is projected that in 2050 the 5 most populous countries are India, China, United States of America (USA), Nigeria, and Pakistan (United Nations, 2022 ). Various high-income countries, such as the United States, are also trending towards a more diverse population group. The white non-Hispanic will account for 47% of the total US population by 2050 while the rest consists of a mix of Hispanic/Latinos, black, and Asian populations signalling a trend towards what is referred to as “minority whites” in the US (Frey, 2018 ; Passel & Cohn, 2008 ). The discussion on diversity is primarily influenced by two contrasting views in which one perspective portrays diversity as a catalyst for growth while the other suggests it hinders growth (Rodríguez-Pose & von Berlepsch, 2019 ). These contrasting perspectives indicate that the approaches to assess the relationship between population diversity and growth are not so straightforward. Several existing studies have shown how diversity has demographic and economic implications. Gören ( 2014 ) showed how ethnic diversity affects economic growth of 100 countries from the 1960—1999 period. The study found that ethnic diversity led to higher fertility rate and indirectly contributed to international trade positively that proved beneficial in rejuvenating declining populations (Gören, 2014 ). Collier ( 2001 ) found that countries characterized by dominance, where one group becomes the majority, have worse economic performance than fractionalized countries, where there are many ethnic groups. For instances, China’s efforts to improve income and education across all ethnic groups still causes income and educational gap to persists among the non-Han ethnic minorities in China or even grew over time (Chia & Hruschka, 2023 ), but simply comparing the Han and non-Han does not paint a full picture in the experience of each minority group. One minority group which is the Man tends to have an overall higher income and education level than the Han, the Buyi have equivalent educational achievement with the Han, while the Miao and Tujia have lower overall achievement than the Han (Chia & Hruschka, 2023 ). Additionally, fractionalized societies also face poorer public sector performance than homogeneous societies (Collier, 2001 ). Ratna et al. ( 2009 ) analyzed the effect of diversity by measuring both racial and linguistic diversity and found mixed results i.e., racial diversity negatively affects Gross State Product (GSP) growth, linguistic diversity positively affects GSP growth. On a similar note, there have been mixed results on how countries with varying income levels are affected by population changes. Montalvo & Reynal-Querol ( 2005 ) found that social polarization, which is the segregation of social groups due to economic factors such as income inequality and social displacement, negatively affects economic growth through the reduction in investment as well as an increase in public consumption and civil wars incidence. Another study by Peterson ( 2017 ) noted that rapid population growth in low-income countries can result in a demographic dividend in the long run as these youths grow to be productive adults. However, the study also noted that growth induced by high fertility rates commonly found in low-income countries reduce overall well-being, while growth induced by decreased mortality rates is viewed more favorably resulting in higher positive impact on savings and economic growth. High-income countries often experience low or negative population growth, which can lead to an ageing population. Higher population growth would alleviate the pressure on the working-age population and the government to support the elderly. However, this is unlikely to happen as fertility rates in high-income countries continue to decline (Peterson, 2017 ). Despite numerous existing research that has specifically analyzed how diversity causes demographic and economic change, studies that specifically analyze the relationship between population diversity and population growth while incorporating both time-variant and cross-country components are limited. To the best of our knowledge, the majority of existing research trade-off with either focusing on time-varying components that is limited to a narrow period at a given area or research with a cross-country component but is mostly limited to a single or multiple non-continuous time period, such as in the case of Ananta et al. ( 2023 ), DiRienzo et al. ( 2007 ), Docquier et al. ( 2020 ), and Rodríguez-Pose & von Berlepsch ( 2019 ). Such analysis could not explain how the relationship between ethnic diversity, population, and income evolves over time and across different countries. Such analysis could not explain how the relationship between ethnic diversity, population, and income evolves over time and across different countries. Understanding this complex relationship would enable policymakers to formulate sound policies that could utilize the benefits of ethnic diversity while also addressing its potential problems. This research attempts to fill this gap in the literature by examining how population diversity influences population growth and income. We utilized a panel dataset consisting of 150 countries ranging from 1960–2013 and analyzed using a dynamic panel regression model, specifically the system Generalized Method of Moments (GMM) method to account for fixed effect and dynamic panel model-specific bias. It also fits in an unbalanced panel data and data that suffers from endogeneity in its variables. Our results confirmed that ethnically diverse populations and migration contribute to the expansion of the population. It may relate to the openness and acceptance of other ethnicities to migrate and the strategic interaction between ethnic groups to compete for influence, thus promoting pronatalism policies, as indicated by the rising fertility rate in such mixed demographic compositions. However, we also found a negative correlation between population diversity and income growth. The result indicates that while diversity may foster population growth, it may not necessarily lead to income growth. This paper is divided into several sections. Section two provides an insight into the literature review. Section three describes the methodology utilized in this research. Section four elaborates on the empirical result and section five concludes this research. 2. Literature Review The discussion on diversity is not a straightforward matter that is often controversial and discussed across a diverse range of disciplines from both natural and social science. The discourse on diversity is dominated by two opposing perspectives with one view depicting diversity as growth-promoting while the other view depicts it as obstructing growth (Rodríguez-Pose & von Berlepsch, 2019 ). Differing perspectives mean the angles in evaluating the link between population diversity and population growth are not uniform, also implying that a variety of parameters as a proxy for diversity are used with a distinct aspect of the notion. The most prevalent proxies for diversity studies include population fractionalization, polarization, and segregation therefore the fact that diversity may either promote or hinder growth depends on the proxy being used (Rodríguez-Pose & von Berlepsch, 2019 ). Literatures on how diversity promotes growth highlight the role of innovations and skills as its key determinants. The movement of migrants from to a host country brings along a novel range of skills, knowledge, and perspectives that are beneficial for nurturing technological innovation and positive economic outcomes (Bove & Elia, 2017 ). For instance, immigrant diversity is positively correlated with economic prosperity with a one percentage point in skilled migrant diversity increases GDP per capita by 2 percent (Alesina, Harnoss, & Rapoport, 2016 ). On a similar note, diversity has also been shown to have positive impact on wages among high-income jobs that demand complex problem-solving skills (Cooke & Kemeny, 2017 ) as well as diversity of high-skilled immigrants on economic growth, as confirmed that there is an increase of 6% in GDP per capita for every 10% increase in high-skilled diversity (Docquier et al., 2020 ). Similar evidence was also found regarding the positive effect of diversity on GDP per capita but this effect is found to be stronger and more consistent among developing countries (Bove & Elia, 2017 ). However, it is necessary to note that diversity has consistently been proven to have no significant effect on economic outcomes for low skilled jobs (Cooke & Kemeny, 2017 ; Docquier et al., 2020 ; Suedekum, Wolf, & Blien, 2014 ). Production specialization is also found to act as a catalyst for diversity promoting growth in the form of trade. Montalvo & Reynal-Querol ( 2021 ) highlighted the positive relationship between ethnic diversity and economic growth due to the increase in inter-ethnic groups' trade activities, specifically in smaller regions, as different ethnic groups have different production preferences. There is a strong argument against discrimination and non-inclusion in the diversity context as, evidently, the exclusion of a sizable population group comes at the severe cost of demographic change related to an ageing population and the growing proportion of traditionally underprivileged groups in the labour market (OECD, 2020 ). Aside from the positive economic outcome of diversity, one literature also suggests that ethnic diversity may induce higher fertility rate leading to population growth, mainly due to political factors. A diverse population leads to strategic interactions among ethnic groups, promoting pronatalism and increasing fertility rates as group leaders incentivize fertility-boosting policies (Papyrakis & Mo, 2014 ). Some evidence also reveals the cost of sustaining non-inclusion of diverse groups. For instance, France could see an increase of around EUR 150 billion over 20 years by increasing employment rates of disadvantaged groups to the average level, translating to a 0.35 percent yearly GDP increase; or reducing the labour force participation gender gap by a quarter across the OECD by 2025 may result in 1 percentage point rise in projected baseline GDP growth from 2013-25 while halving the gap could result in an almost 2.5 percentage point increase (OECD, 2017 ). A common theme among the literature arguing that diversity promotes growth is that the diversity is based on the number of different population groups within an area with variation based on language, religion, and ethnicity. These literatures incline to use a fractionalization index as a measure of population diversity. The idea of a fractionalization index presumes that the greater the number of ethnic groups, the higher the diversity in a society thus positively inducing the potential for the growth of economic outcome (Rodríguez-Pose & von Berlepsch, 2019 ). Unfortunately, these fractionalization indices and preceding literature on diversity usually do not consider the size and distance of different ethnic groups. Additionally, most studies emphasize more on evaluating how diversity affects the outcome within a country or even at an individual level, indicating the lack of studies that incorporate an examination at a wide cross-country level. The opposite view that argues diversity inhibits growth considers diverse groups to be the main destabilizing factor with the potential to escalate into a social turmoil or conflict. Literature that suggests diversity inhibits growth includes fractionalization as a proxy for diversity similar to the growth-promoting group but places increasing emphasis on segregation and polarization indices (Rodríguez-Pose & von Berlepsch, 2019 ). The cost of fractionalization on a macroeconomic scale has been empirically ingrained as measured through the ethno-linguistic diversity lens in a study by Easterly & Levine ( 1997 ) that discovers ethnic fragmentation is associated with lower economic growth, particularly in Africa, mainly due to the frequent ethnic conflict occurring in the region. Consequently, this diversity causes rent-seeking behaviour among different groups that further undermine efforts to adopt sound public policies as well as resulting in poor education attainment, high financial debt, and low infrastructure quality as a result of high segregation levels. Gören ( 2014 ) further highlighted the negative direct consequence of ethnic diversity on economic growth, the indirect negative consequence of ethnic polarization on economic outcome through human capital, investment, trade openness, and civil war, as well as noting that ethnically diverse countries possess a higher average fertility rate. One study further examines the effect of diversity by separating between dominance, in which one group becomes the majority, and fractionalization, where there are many ethnic groups. Collier ( 2001 ) finds that countries characterized by dominance are found to have worse economic performance than fractionalized countries, which are generally non-problematic in democracies but can be damaging in dictatorship. Additionally, fractionalized societies also face poorer public sector performance than homogeneous societies (Collier, 2001 ). Moreover, Montalvo & Reynal-Querol ( 2021 ) concludes that social polarization negatively affects economic growth through the reduction in investment, increase in public consumption and civil wars incidence. Meanwhile, Ratna et al. ( 2009 ) studied the macroeconomic effects of social diversity across 48 states in the United States (US), finding mixed empirical results for the effect of diversity on Gross State Product (GSP) per capita growth while racial diversity decreases GSP growth and linguistic diversity increases GSP growth. There are mixed results on how countries with varying income levels are affected by population changes. According to Peterson ( 2017 ), rapid population growth in low-income countries can lead to short and medium-term challenges due to a larger young population but can result in a demographic dividend in the long run as these youths grow to be productive adults. However, the study also finds that growth induced by high fertility rates commonly found in low-income countries reduce overall well-being, while growth induced by decreased mortality rates is viewed more favorably resulting in higher positive impact on savings and economic growth. In contrast, low or even negative population growth found in high-income countries can result in an ageing population, putting burden on the productive age group and government to support the elderly population (Peterson, 2017 ). Once again, there is a common theme among the literature that establishes the fact that diversity inhibits growth. Diversity is emphasized as the cause of the negative consequences of polarization and segregation and separate indices have been used to investigate these consequences from a distinct aspect of diversity altogether. Polarization indices focus more on the size of one group to another and the distance separating them rather than the quantity of groups within a given population. Groups with more distance amongst each other would have more similarity in size and a stronger separation between groups reduce communications which negatively affects economic development due to diversity (Rodríguez-Pose & von Berlepsch, 2019 ). The diverse culture pervasive among different groups affects trust, disturbing the coordination of economic actors and their interaction, as well as enlarging the gap in preferences and giving rise to conflict. Nevertheless, the interaction among diverse groups concurrently generates a myriad of experiences, skills, and knowledge that advances technological innovation and ideas, increase productivity and quality of goods and services, as well as procreation of society (Alesina et al., 2016 ; Rodríguez-Pose & von Berlepsch, 2019 ). Aligning with most of the previous research, this study will focus on a single dimension, which is ethnic diversity that is measured by the Historical Index of Ethnic Fractionalization (HIEF) (Drazanova, 2019 ). The HIEF is defined as the probability that two randomly chosen individuals in the same country do not share the same ethnicity. This variable is used to measure the degree of population diversity in a country, which is the main independent variable in this research. This variable is used to measure the degree of population diversity in a country, which is the main independent variable in this research. The dependent variables, namely population growth and income growth, are measured by the population growth and GNI per capita variable that are sourced from the World Bank Dataset. The use of GNI per capita as a proxy to income growth has been previously observed in empirical literature (Janvry & Sadoulet, 2000). The control variables in this research, namely population density, fertility rate, mortality rate, age structure, net migration, and sex ratio, are selected by examining earlier literature and theoretical arguments. According to Malthus, from his book titled “An Essay on the Principle of Population”, higher population size will limit the available resources for each person, which leads to decrease in population growth. Both fertility rate and mortality rate is found to affect economic growth, which is closely related to income growth (Ashraf, Weil, & Wilde, 2013 ; Zhang, Zhang, & Lee, 2001 ). Furthermore, Ozgen et al. ( 2010 ) have established that net migration is positively correlated with per capita income growth. Meanwhile, Imbalanced sex ratio is also found to negatively affect birth rate which leads to decrease in population growth (Hesketh & Xing, 2006 ). Additionally, an increase in sex ratio at birth that tends to skew the proportion between male and female will significantly reduce economic growth in the short and long-term (Wu, Ali, Zhang, Chen, & Hu, 2022 ). Moreover, female labour force participation rate has a negative effect on population growth through the reduction in fertility rate, since women that are involved in the labor force tend to delay their childbearing due to the work’s demands (Rafique Umar & Shoaib, 2015). On the other hand, an increase in the female labour force participation rate is found to have a positive and significant effect on economic well-being (Tsani, Paroussos, Fragiadakis, Charalambidis, & Capros, 2013 ). 3. Methodology 3.1 Data The panel dataset that is utilized in this research consists of 150 countries from 1960—2013, considering the availability of the latest data from the World Bank Dataset, Historical Index of Ethnic Fractionalization (HIEF) dataset that is derived from the Cline Center for Democracy Composition of Religious and Ethnic Groups (CREG) that is further extended by Drazanova ( 2020 ) to account for cross country and time-varying effect, and International Labour Organization (ILO). The Historical Index of Ethnic Fractionalization (HIEF) represents the proxy for diversity ( EF it ). The index has a ratio between 0 (complete homogeneity) and 1 (complete heterogeneity). The population density ( PD it ) is defined as the quantity of people per square kilometre of land area in a given year and period, the fertility rate ( FR it ) is represented by the total fertility rate or the total number of births per woman during her childbearing years in a given country and period, mortality rate ( MR it ) is represented by the infant mortality rate or the death of an infant before 1 year of age for every 1000 live births in a given country and period, net migration ( Mig it ) is obtained from the number of immigrants minus the number of emigrants including citizens and noncitizens in a given country and period, the sex ratio ( Sex it ) utilizes the sex ratio at birth or the ratio of male births per female births on a 5 year average in a given country and period. All the aforementioned data were obtained from the World Development Indicator from the World Bank Database. Finally, the female labour force participation rate ( FLC it ) was obtained from a combination of data from the International Labour Organization (ILO) estimates and complemented by the national estimates of respective countries in a given period. The countries consist of 49 countries from Africa, 43 from Asia, 38 from Europe, 3 from North America, 4 from Oceania, and 13 from South America. Measuring diversity has proven to be a challenge due to data limitations. On the following note, diversity could be defined in many terms since any person could be categorized into multiple groups, such as gender, age, religion, ethnicity etc. Therefore, the majority of economic analyses about diversity focus on only one dimension (OECD, 2020 ) and in this research we focus specifically on how ethnic diversity relates to population growth and income. 3.2 Empirical Strategy In order to investigate how population diversity may be related with population growth and income growth, the following equation is used to perform the estimation: $${y}_{it}={\alpha }_{0}+{\beta }_{1}{EF}_{it}+{\beta }_{2}{PD}_{it}+{\beta }_{3}{FR}_{it}+{\beta }_{4}{MR}_{it}+{\beta }_{5}{Mig}_{it}+{\beta }_{6}{Sex}_{it}+{\beta }_{7}{FLC}_{it}+{\vartheta }_{i} +{\epsilon }_{it}$$ (1) where y it refers to both the population growth (Model A) and gross national income per capita (Model B) as the dependent variables in country i and year t . Notation EF it is the independent variable that refers to the HIEF. Meanwhile, PD it , FR it , MR it , Mig it , Sex it , and FLC it are a set of control variables that consist of population density, fertility rate, mortality rate, net migrations, sex ratio, and female labour force participation respectively. Finally, 𝜗 i and ε it are the country-specific effect and error term. Among the data, some adjustments are necessary to allow a proper estimation for the model by transforming to natural logarithm. These consist of the net migrations ( Mig it ) data, the gross national income data, and the population density ( PD it ) data. To perform the estimation above, the dynamic panel regression method is chosen. This decision is made by considering the two following issues as stated by OECD ( 2020 ). First, the issue of unobserved heterogeneity could affect both the outcome variable and ethnic diversity and can lead to bias in the estimated effects of diversity (Alesina & Ferrara, 2005). Second, there is a limited amount of research that has established the causal relationship between diversity and economic outcomes by utilizing the instrumental variables (IV) estimation. The dynamic panel regression method, which allows the use of the lag value of the variable in the model, is capable in overcoming issues in the cross-sectional type model that arise from the country-specific and time-specific unobserved variables that lead to omitted variable bias and endogeneity problem (Levine, Loayza, & Beck, 2000 ). Among the various dynamic panel regression methods, Generalized Method of Moments (GMM) method is found to be able to tackle various issues in model estimation, such as fixed effect, endogeneity, and dynamic panel model-specific bias. The flexibility of this method enables it to be used in an unbalanced panel data and data that suffers from endogeneity in its variables. The capability to tackle various issues and estimation problems leads to the widespread use of GMM, mainly difference GMM and system GMM in empirical literature (Rahman, Rana, & Barua, 2019 ; Roodman, 2009 ). This research specifically prefers using the system Generalized Method of Moments (GMM) over the difference GMM for conducting model estimation. The system GMM method allows for estimation in both first difference and level forms, whereas the difference GMM method only utilizes the first-difference form for its estimation. This distinction in characteristics results in higher precision, efficiency, and lower bias from the system GMM approach compared to the difference GMM method, particularly when dealing with small panel data (Soto, 2009 ). This observation aligns with the findings of Bond ( 2002 ) who concludes that the difference GMM method is more susceptible to finite sample bias than the system GMM method. These limitations have led to a greater preference in the empirical literature for using the system GMM approach over the difference GMM. For instance, Levine et al. ( 2000 ), Rahman et al. ( 2019 ), and Zarra-Nezhad et al. ( 2014 ) have opted for the system GMM method for model estimation after comparing it to the difference GMM method in order to mitigate potential issues in their research. The preference for using the system GMM approach is also evident in literature discussing similar topics. Choudhury & Sahu ( 2022 ), in their examination of the role of ethnic fragmentation on the relationship between fiscal decentralization and government size, employ the system GMM method as one of their research techniques. Additionally, Ajide et al. ( 2019 ), who investigate the mediating role of institutions in the nexus between ethnic diversity and inequality, also utilize the system GMM method alongside pooled OLS and fixed effects methods. In ensuring the robustness of our model, we introduce an additional variable which categorizes countries based on income level, following the World Bank historical classifications by income as of 2013 according to the latest available period in our dataset. The equation is as follows: $${y}_{it}={\alpha }_{0}+{\beta }_{1}{EF}_{it}+{\beta }_{2}{PD}_{it}+{\beta }_{3}{FR}_{it}+{\beta }_{4}{MR}_{it}+{\beta }_{5}{Mig}_{it}+{\beta }_{6}{Sex}_{it}+{\beta }_{7}{FLC}_{it}+{\beta }_{8}{IC}_{i}+ {\vartheta }_{i} +{\epsilon }_{it}$$ 2 where y it refers to the population growth (Model C) and gross national income per capita (Model D) as the dependent variables in country i and year t . The additional categorical variable to indicate country’s income class is represented with ICi. This variable also provides a clearer view of understanding the relationship between diversity, population growth, and income growth by factoring in the country’s income level. 4. Results and Discussions 4.1 Descriptive Statistics A closer look at the data shows that both South Korea and North Korea have the lowest Historical Index of Ethnic Fractionalization (HIEF) value, measuring at 0 in the 1960s. Even in the latest available data of 2013, both countries still had relatively low HIEF values at 0.095 for South Korea and 0.02 for North Korea. Meanwhile, African countries are found to be highly diverse in terms of ethnic groups, such as Liberia, Uganda, and Togo, with HIEF values measuring at 0,89, 0,88, and 0,87 respectively. The complete list of countries along with their HIEF rankings at the earliest and latest available year are available at the Appendix . Table 1 Descriptive Statistics Variable Obs Mean Std. Dev. Min Max Population Growth 8,108 1.909 1.770 -27.722 19.360 GNI per Capita 3,526 9805.006 14023.18 189.518 86012.46 HIEF 7,287 0.440 0.270 0 0.89 Log Population Density 6,150 3.848 1.389 -0.098 8.940 Fertility Rate 8,262 4.215 2.065 1.078 8.25 Mortality Rate 7,479 56.984 47.040 2.1 228.9 Log Migration 8,262 14.582 0.185 0 15.209 Sex Ratio 8,262 1.049 0.018 1.003 1.178 Female Labor Participation Rate 4,060 48.509 16.066 2.44 93.13 Further inspection based on scatter plots to examine the association between HIEF, population growth, and GNI per capita shows a tendency for population growth to be higher in ethnically diverse populations, adjusting for outliers. Meanwhile, higher GNI per capita is observed more in lower diversity settings. These results signify the potential of a positive correlation between HIEF and population growth and a negative correlation between HIEF and income growth. Graph 1. Scatter Plot of HIEF and Population Growth Graph 2. Scatter Plot of HIEF and Income Growth 4.2 Regression Results Based on the baseline results in Table 2 below, population diversity represented by the HIEF is positive and statistically significant at 1% to population growth. In model A, the fertility rate and net migration are positively correlated to population growth while the mortality rate is negatively correlated to population growth. All three of the previously mentioned control variables are statistically significant at the 1% level. Conversely, population density and sex ratio show no significant relationship to population growth. On a similar note, population diversity also shows a statistical significance at 1% level but negative relationship to income growth. In model B, population density, mortality rate, and sex ratio are negatively correlated with income growth at the 5%, 1%, and 5% significance level respectively. Fertility rate and net migration in model B do not show any significant relationship to income growth. Additionally, female labour force participation has also been shown to be statistically significant at 5% and having an inverse relationship with population growth in model A while showing no relationship at all with income growth in model B. Table 2 System GMM Baseline Estimation Results Dependent: Population Growth Dependent: Income Growth Diversity (HIEF) 2.0661*** (0.7959) -2.0308*** (0.56511) Log Population Density 0.1818 (0.1750) -0.2188** (0.1035) Fertility Rate 0.8115*** (0.1815) -0.1747 (0.1504) Mortality Rate -0.0259*** (0.0085) -0..0301*** (0.0079) Log Net Migration 3.0876*** (1.1253) 0.1849 (0.3058) Sex Ratio -7.1887 (9.0649) -12.7315** (5.0046) Female Labor Participation Rate -0.0232 ** (0.0097) 0.0042 (0.0084) Constants -38.1278 ** (17.9830) 22.1870*** (7.1313) Observations 3946 2564 Countries 150 127 Notes: Standard errors are shown in parentheses. ***, **, and * show significant level of 1%, 5%, and 10% respectively. The main findings indicate that ethnic diversity is statistically significant on both population growth and income growth. Diversity has a positive correlation with population growth and a negative correlation with income growth. The positive correlation of diversity with population growth aligns with Gören ( 2014 ) which concludes that diversity leads to higher population growth through fertility rates. Papyrakis & Mo ( 2014 ) provides an explanation for this phenomenon that a more diverse population could foster strategic interaction among ethnic groups to compete for influence within the society. To gain more influence, ethnic group leaders may promote pronatalism policy to increase the number of population within the ethnic group, thus elevating their position and dominance in the society. As a result, this will enhance the fertility rate and end up increasing the population growth in the highly diverse society. Similar explanation is also pointed out by Janus ( 2013 ) who argues that ethnic groups may promote higher fertility rate to increase their voting power relative to other groups. Janus ( 2013 ) also further specifies that weak political institutions are the key factor in the emergence of this condition, using fertility rates as the key to increase ethnic political power. The negative correlation found in income growth is supporting the view that diversity inhibits economic development. The results are in line with Easterly & Levine ( 1997 ) who also identified a negative association between ethnic fragmentation and economic growth due to the frequent ethnic conflict occurring in the highly diverse region. Diverse society is prone to exhibit a propensity for rent-seeking behaviour, which hinders the effective formulation and implementation of sound public policies. This can lead to adverse consequences, such as poor education attainment, high financial debt, and low infrastructure quality, due to heightened levels of societal segregation. Gören ( 2014 ) also elucidated the adverse direct impact of ethnic diversity on economic growth and the indirect repercussions of ethnic polarization on economic outcomes through four channels, namely human capital accumulation, investment levels, trade openness, and the proclivity towards civil conflict. In Gören ( 2014 ), it was stated that education, as one form of human capital accumulation, may not be properly and fairly distributed in an ethnically diverse environment due to the government’s intention of using education as a tool to control and influence particular ethnic groups. This situation may lead to lower schooling levels which negatively affects human capital and income growth. Easterly & Levine ( 1997 ) also noted that diverse societies may be less satisfied with the quality of education due to the disagreements between ethnic groups on the characteristics and aspects of the education itself, such as the language used and the learning materials which could lead up to less investment in human capital. Ogbu & Simons ( 1998 ) further pointed out that minority groups are more likely to become suspicious of the public schools that are considered to favor the ruling ethnic group and discriminate against the minorities, thus discouraging them to take on schooling. The next channel, level of investment, has been partially explained by Easterly & Levine ( 1997 ) in the previous discussion. Countries with highly diverse populations are prone to rent-seeking behaviour by each ethnic group. These rent-seeking activities may generate conflict of interest and lead to a problem in reaching an agreement on the kind of public goods that will be provided to the society due to the disharmony between ethnic groups. As a result, this will hinder the development of public infrastructure, education institutions, healthcare, and government policy. This disruption would reduce the level of investment in the productive sector, which will weaken the economic growth and income growth. Ethnic diversity could also affect the economy through free trade channels. Regions with higher ethnic diversity are found to have lower quality of exported goods than the lower ethnic diversity regions due to the difficulties in communicating and collaborating between ethnic groups to produce high quality differentiated products (Luong, 2021 ). Lower quality of exported goods will weaken the export sector and lead to lower income from export activities. Another channel, which is civil war, has also been identified to hamper economic development and tends to happen in ethnically diverse countries. According to Collier ( 2001 ), civil war could rapidly escalate and cause human and physical capital destruction and also mass exodus of the educated population. The consequences of this would severely inhibit the country’s human development and the economy as the country is unable to function properly. Furthermore, an increased level of ethnic diversity can lead to fierce competition for jobs among different ethnic groups. In an ideal scenario, this heightened competition should act as a filter for employers to recruit the most competent applicants. As a result, this competitive environment can be beneficial for highly skilled workers. However, those who are unsuccessful in this competition and have already relocated to these regions may find themselves settling for lower-tier jobs, which subsequently leads to lower earnings according to the statistical discrimination theories (Horvath & Huber, 2019 ). Additionally, DiRienzo et al. ( 2007 ) found that countries with higher ethnic diversity tend to be less competitive. Consequently, lower competitiveness means having lower productivity and this causes a country’s likelihood of sustained growth to be lower than more competitive countries, also causing the quality of labour to also be less competitive. Based on the estimation result, another interesting point should be highlighted. Previous discussion has stated that ethnic diversity can have a positive or negative effect on the economy depending on the variable that is used as a measure (Rodríguez-Pose & von Berlepsch, 2019 ). Empirically, ethnic fractionalization measure is generally related to higher economic growth, while ethnic polarization measure is frequently related to lower economic growth (Ananta et al., 2023 ). The results of our estimation that shows a negative correlation between ethnic diversity, as measured by ethnic fractionalization index, and economic growth do not support the general conclusions that are found in the literature. The baseline estimation results above do not describe the full picture as it only shows how population growth and income per capita growth (GNI per capita) is explained by population diversity and other control variables at a global scale. To obtain a more accurate description of the aforementioned condition, we show how population diversity relates with population growth and income per capita growth by categorizing it based on the World Bank historical classifications by income as of 2013, following the latest available data for this research. Table 3 System GMM Estimation Results with Income Level Classification Dependent: Population Growth Dependent: Income Growth Diversity (HIEF) 2.4310 *** (0.8265) -0.8350 ** (0.3960) Log Population Density 0.2108 (0.1620) -0.0929 ** (0.0444) Fertility Rate 0.8962*** (0.1712) -0.0684 (0.0881) Mortality Rate -0.0180** (0.0073) -0.0081** (0.0041) Log Net Migration 2.8950*** (1.0204) 0.1345 (0.1253) Sex Ratio -8.9130 (8.8632) -12.5981 *** (3.2192) Female Labour Participation Rate -0.0183 ** (0.0083) 0.0148 ** (0.0061) Interaction Variable: Middle-Income to Low-Income Countries 0.8684* (0.4796) 1.3814*** (0.3566) Interaction Variable: High-Income to Low-Income Countries 1.6536*** (0.5497) 3.0056*** (0.3543) Constants -17.6425** (6.5861) 14.0091 ** (5.3010) Observations 778 471 Countries 150 127 Notes: Standard errors are shown in parentheses. ***, **, and * show significant level of 1%, 5%, and 10% respectively. Table 3 above shows the relationship between population diversity and population growth as well as population diversity and income growth with the addition of a categorical variable based on countries income level, which also acts as a robustness measure of our baseline estimation. With the addition of a categorical variable, the results in model C illustrate that population diversity is statistically significant to both population growth and income growth which is consistent with the previous baseline estimation result. Other independent variables in model C consisting of fertility rate, net migration, as well as the high-income categorical variable are positive and statistically significant towards population growth while mortality rate and female labour force participation are negative and statistically significant towards population growth as the dependent variable. Conversely, population density, sex ratio, and middle-income categorical variable are shown to not have any significant relationship with population growth. On the other hand, the results in model D show that population density, mortality rate, and sex ratio show a negatively significant relationship with income growth as the dependent variable while female labour force participation, middle-income, and high-income categorical variable are positively significant towards income growth. Fertility rate and net migration are the independent variables that are not statistically significant towards income growth as the dependent variable. Our estimation that involves the income class categorical variable highlights the importance of the significant relationship between diversity and population growth as this particular situation has been plaguing high-income economies, which may potentially cause social and economic problems if left alone (Peterson, 2017 ). Model C in Table 3 shows a positive significant relationship between diversity and population growth at the 1% level. At the same time, fertility rate, mortality rate, and net migration respectively are all showing statistical significance towards population growth. Fertility rate and net migration exhibit positive relationships towards population growth. It is also worth noting that female labour force participation causes a positive income growth and this relationship is statistically significant at the 5% level. The estimation results also reveal a consensus across countries at all income levels that net migration is correlated with a positive relationship towards population growth. On the other hand, it has been proven that the historical decline in world population due to falling fertility rates occurred in response to higher levels of economic development (Murdoch, Chu, Stewart-Oaten, & Wilber, 2018 ). In general, the high population growth often found in low-income economies and the low population growth in high-income economies are likely to cause social and economic inequalities as well as inhibit development efforts (Peterson, 2017 ). While international migration may help in adjusting these imbalances, such policies are often opposed by many and quite unpopular (Peterson, 2017 ). The primary reason for the unpopular view of migration is, among others, due to the perceived low labour quality of migrants, political, and sociocultural differences. However, such views may not always reflect the actual migrants’ economic contributions. In fact, the perceived negative effects of immigrants are often baseless and create a dilemma as most migrants’ destination countries could benefit with more human capital and expertise brought by immigrants (OECD/ILO, 2018 ). Therefore, increased efforts to improve the overall well-being of less wealthy populations across the world are vital to solving the dilemma between the perceived low labour quality of migrants and plummeting population of a country (Murdoch et al., 2018 ; OECD/ILO, 2018 ). Additionally, asylum process claims which are commonly faced by refugee migrants, who are most consistently considered as low labour quality on arrival, should be kept short as this has a strong impact on their future labour outcomes and facilitating them to join the labour market at the earliest possible stage helps to minimize skill losses and increases the effectiveness of human capital investment (Brell, Dustmann, & Preston, 2020 ). This is particularly relevant in light of Gören’s ( 2014 ) findings as prolonged asylum processes may exacerbate disparities in human capital accumulation through education in ethnically diverse environments, leading to an inequitable distribution of resources due to government policies targeting specific ethnic groups. We also found that female labour force participation is statistically significant and positive towards income growth implying that there has indeed been a shift in paradigm of how people in high-income countries think about posterity and labour market conditions. Initial fertility models in the past decades across many countries were developed to sufficiently explain two consistent trends: lower fertility rates mean higher income and higher women's workforce participation (Doepke et al., 2022 ). However, our finding on female labour force participation indicate that these facts seem to be changing in recent times as some observation by Doepke et al. ( 2022 ) has confirmed the positive relationship between fertility and income, implying that women are more active in the workforce while still maintaining the same or even achieve higher level of income. Furthermore, such trends are also supported by flexible labour market conditions with favorable family policies, especially towards women, and changing social norms with fathers caring for their children. Policymakers should consider the effects of population diversity on population growth and income growth when designing and implementing policies that affect these outcomes. Adopting a dynamic and context-specific approach to those three aspects is also important as these factors may vary over time and across countries. For example, policies that aim to expand the population of advanced economies or reduce the population growth of developing economies may need to account for the different preferences, behaviours, and incentives of diverse ethnic groups in society. It is also worth pointing out that policies may work well only in certain countries or certain time periods which further reinforce the need for policymakers to assess and adjust their policies accordingly. Additionally, policymakers’ awareness should also be raised regarding the potential challenges and opportunities that population diversity brings to social cohesion, political stability, and economic development. For instance, policies that promote interethnic cooperation, integration, inclusion, and equitable distribution of income may help to mitigate the negative effects of ethnic conflict, rent-seeking, and policy inefficiencies in highly diverse settings. Meanwhile, policies that foster ethnic diversity, recognition, and representation may help to enhance the positive effects of cultural diversity, innovation, and creativity in society. 5. Conclusions Our research sheds light on the relationship between population diversity and population growth with an additional focus on the relationship between population diversity and income. The dataset spans from 1960–2013 and includes 150 countries: 49 from Africa, 43 from Asia, 38 from Europe, 3 from North America, 4 from Oceania, and 13 from South America. We confirmed that ethnically diverse populations and migration contribute to the expansion of the population. It may relate to the consensus that regions with diverse ethnic populations are known for their open social dynamics, making them pleasant places to reside and drawing new ethnicities to move in. Diverse populations could also be associated with an increase in strategic interaction between ethnic groups to compete for influence, thus promoting pronatalism policies, which is indicative of a heightened fertility rate within such varied demographic compositions. However, we also found a negative correlation between population diversity and income growth. This can be explained due to the adverse direct impacts of ethnic diversity on economic growth through various potential channels and the correlation between ethnic diversity, lower competitiveness and productivity, which in turn may reduce a country's potential for sustained growth and labour quality. The result indicates that while diversity may foster population growth, it may not necessarily lead to income growth. It is worth pointing out that this study only used HIEF as the proxy variable for ethnic diversity. Therefore, the results may not accurately capture the full extent of the correlation between ethnic diversity, population growth, and income growth. Declarations The authors are grateful to a colleague for helpful comments and assistance. 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Journal of Public Economics , 80 (3), 485–507. https://doi.org/https://doi.org/10.1016/S0047-2727(00)00122-5 Appendix Historical Index of Ethnic Fractionalization (HIEF) Ranking in 1960 and 2013 respectively Ranking Country Year HIEF Ranking Country Year HIEF 1 Liberia 1960 0.887 1 Liberia 2013 0.889 2 Togo 1960 0.884 2 Uganda 2013 0.883 3 Nigeria 1960 0.868 3 Togo 2013 0.88 4 South Africa 1960 0.853 4 Nepal 2013 0.86 5 Mali 1960 0.846 5 South Africa 2013 0.856 6 Philippines 1960 0.819 6 Chad 2013 0.855 7 D.R. of Congo 1960 0.816 7 Kenya 2013 0.855 8 Chad 1960 0.805 8 Mali 2013 0.852 9 Nepal 1960 0.804 9 Nigeria 2013 0.85 10 Senegal 1960 0.803 10 Guinea-Bissau 2013 0.808 11 Ethiopia 1960 0.803 11 Philippines 2013 0.807 12 Benin 1960 0.782 12 Indonesia 2013 0.803 13 Gabon 1960 0.77 13 East Timor 2013 0.802 14 Yugoslavia 1960 0.756 14 Sierra Leone 2013 0.801 15 Guinea 1960 0.752 15 Malawi 2013 0.791 16 Sudan 1960 0.745 16 Central African Republic 2013 0.79 17 Cote d'Ivoire 1960 0.744 17 Gabon 2013 0.789 18 Ghana 1960 0.736 18 Ethiopia 2013 0.783 19 Central African Republic 1960 0.733 19 Angola 2013 0.779 20 Burkina Faso 1960 0.73 20 Burkina Faso 2013 0.767 21 Iran 1960 0.73 21 Kuwait 2013 0.765 22 Indonesia 1960 0.709 22 Benin 2013 0.764 23 Congo 1960 0.7 23 Afghanistan 2013 0.763 24 Niger 1960 0.683 24 Gambia 2013 0.762 25 Canada 1960 0.682 25 Namibia 2013 0.76 26 USSR 1960 0.665 26 Pakistan 2013 0.748 27 Ecuador 1960 0.665 27 Senegal 2013 0.747 28 Colombia 1960 0.657 28 Sudan 2013 0.746 29 Peru 1960 0.637 29 Iran 2013 0.743 30 Trinidad and Tobago 1960 0.625 30 Ghana 2013 0.736 31 Bolivia 1960 0.614 31 Cote d'Ivoire 2013 0.731 32 Malaysia 1960 0.601 32 Canada 2013 0.73 33 Guatemala 1960 0.598 33 Guinea 2013 0.727 34 Mauritania 1960 0.59 34 Mauritania 2013 0.713 35 Afghanistan 1960 0.586 35 Qatar 2013 0.708 36 Pakistan 1960 0.585 36 Zambia 2013 0.706 37 Brazil 1960 0.57 37 Congo 2013 0.704 38 Laos 1960 0.562 38 Democratic Republic of Congo 2013 0.7 39 Mexico 1960 0.539 39 Guyana 2013 0.695 40 Belgium 1960 0.515 40 United Arab Emirates 2013 0.684 41 Chile 1960 0.514 41 Spain 2013 0.669 42 Bhutan 1960 0.502 42 Niger 2013 0.666 43 Panama 1960 0.497 43 Eritrea 2013 0.659 44 Czechoslovakia 1960 0.478 44 Trinidad and Tobago 2013 0.655 45 Nicaragua 1960 0.465 45 Bhutan 2013 0.651 46 Venezuela 1960 0.457 46 Djibouti 2013 0.649 47 Morocco 1960 0.453 47 Colombia 2013 0.639 48 Cuba 1960 0.451 48 Bosnia-Herzegovina 2013 0.637 49 Sri Lanka 1960 0.451 49 Laos 2013 0.634 50 Spain 1960 0.438 50 Peru 2013 0.618 51 Myanmar 1960 0.433 51 Panama 2013 0.612 52 Dominican Republic 1960 0.405 52 Oman 2013 0.597 53 Mongolia 1960 0.4 53 Belgium 2013 0.592 54 Thailand 1960 0.387 54 Tanzania 2013 0.591 55 Singapore 1960 0.385 55 Myanmar 2013 0.59 56 Iraq 1960 0.366 56 Mexico 2013 0.587 57 Cyprus 1960 0.336 57 Bahrain 2013 0.582 58 United Kingdom 1960 0.309 58 Bolivia 2013 0.572 59 D.R. of Vietnam 1960 0.264 59 Malaysia 2013 0.57 60 Costa Rica 1960 0.26 60 Morocco 2013 0.566 61 United States of America 1960 0.259 61 Macedonia 2013 0.562 62 Bulgaria 1960 0.249 62 Brazil 2013 0.559 63 Romania 1960 0.236 63 Latvia 2013 0.547 64 Republic of Vietnam 1960 0.233 64 Nicaragua 2013 0.544 65 Cambodia 1960 0.231 65 Kazakhstan 2013 0.538 66 Switzerland 1960 0.23 66 Ecuador 2013 0.528 67 Israel 1960 0.222 67 Fiji 2013 0.528 68 Uruguay 1960 0.211 68 United States of America 2013 0.527 69 Syria 1960 0.199 69 Turkey 2013 0.521 70 El Salvador 1960 0.197 70 Venezuela 2013 0.52 71 Saudi Arabia 1960 0.195 71 Cuba 2013 0.517 72 Taiwan 1960 0.195 72 Guatemala 2013 0.511 73 New Zealand 1960 0.185 73 Kyrgyz Republic 2013 0.487 74 Yemen Arab Republic 1960 0.18 74 New Zealand 2013 0.485 75 Rwanda 1960 0.164 75 Mauritius 2013 0.466 76 Oman 1960 0.154 76 Estonia 2013 0.458 77 Honduras 1960 0.153 77 Dominican Republic 2013 0.453 78 Libya 1960 0.142 78 Iraq 2013 0.446 79 Turkey 1960 0.13 79 Cape Verde 2013 0.442 80 Lebanon 1960 0.125 80 Chile 2013 0.439 81 Finland 1960 0.117 81 Moldova 2013 0.427 82 Sweden 1960 0.117 82 Zimbabwe 2013 0.415 83 Haiti 1960 0.108 83 United Kingdom 2013 0.399 84 Paraguay 1960 0.105 84 Costa Rica 2013 0.398 85 China 1960 0.101 85 Serbia 2013 0.396 86 Tunisia 1960 0.1 86 Botswana 2013 0.395 87 German Federal Republic 1960 0.086 87 Singapore 2013 0.395 88 Albania 1960 0.07 88 Swaziland 2013 0.39 89 Ireland 1960 0.068 89 Russia 2013 0.376 90 Somalia 1960 0.066 90 Israel 2013 0.376 91 Argentina 1960 0.066 91 Taiwan 2013 0.373 92 Austria 1960 0.06 92 Algeria 2013 0.372 93 Hungary 1960 0.052 93 Ukraine 2013 0.37 94 Greece 1960 0.045 94 Switzerland 2013 0.367 95 Italy 1960 0.041 95 Georgia 2013 0.367 96 Jordan 1960 0.035 96 Tajikistan 2013 0.367 97 German Democratic Republic 1960 0.031 97 Netherlands 2013 0.354 98 Poland 1960 0.027 98 Thailand 2013 0.352 99 Norway 1960 0.021 99 Cyprus 2013 0.347 100 Australia 1960 0.021 100 Sri Lanka 2013 0.323 101 Netherlands 1960 0.013 101 Mongolia 2013 0.315 102 Denmark 1960 0.012 102 Lesotho 2013 0.313 103 Japan 1960 0.012 103 Uzbekistan 2013 0.313 104 Madagascar 1960 0.005 104 Belarus 2013 0.309 105 Egypt 1960 0.003 105 Burundi 2013 0.308 106 Portugal 1960 0.001 106 Bulgaria 2013 0.289 107 Democratic People's Republic of Korea 1960 0 107 Lithuania 2013 0.284 108 Republic of Korea 1960 0 108 Rwanda 2013 0.28 109 Australia 2013 0.276 110 Democratic Republic of Vietnam 2013 0.263 111 Czech Republic 2013 0.262 112 Libya 2013 0.259 113 Slovenia 2013 0.258 114 Turkmenistan 2013 0.255 115 Austria 2013 0.248 116 Slovakia 2013 0.241 117 Hungary 2013 0.232 118 Honduras 2013 0.229 119 Saudi Arabia 2013 0.224 120 Somalia 2013 0.222 121 Portugal 2013 0.22 122 Sweden 2013 0.219 123 Syria 2013 0.213 124 Jamaica 2013 0.21 125 Romania 2013 0.207 126 Madagascar 2013 0.194 127 China 2013 0.19 128 German Federal Republic 2013 0.189 129 Paraguay 2013 0.179 130 Denmark 2013 0.177 131 Uruguay 2013 0.176 132 Ireland 2013 0.174 133 Croatia 2013 0.171 134 Greece 2013 0.167 135 El Salvador 2013 0.165 136 Argentina 2013 0.158 137 Cambodia 2013 0.158 138 Norway 2013 0.151 139 Albania 2013 0.139 140 Finland 2013 0.138 141 Lebanon 2013 0.133 142 Yemen Arab Republic 2013 0.126 143 Azerbaijan 2013 0.122 144 Italy 2013 0.11 145 Haiti 2013 0.105 146 Solomon Islands 2013 0.097 147 Republic of Korea 2013 0.095 148 Poland 2013 0.069 149 Comoros 2013 0.054 150 Armenia 2013 0.045 151 Jordan 2013 0.044 152 Egypt 2013 0.041 153 Tunisia 2013 0.034 154 Bangladesh 2013 0.025 155 Democratic People's Republic of Korea 2013 0.02 156 Japan 2013 0.019 Additional Declarations The authors declare no competing interests. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4115318","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":280427611,"identity":"060fe6b2-a02b-48ae-adae-864c00ebd275","order_by":0,"name":"Irfan Aziz Al Firdaus","email":"data:image/png;base64,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","orcid":"https://orcid.org/0009-0003-8910-9079","institution":"Department of Economics, Faculty of Economics and Business, Universitas Gadjah Mada, Yogyakarta, Indonesia","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Irfan","middleName":"Aziz Al","lastName":"Firdaus","suffix":""},{"id":280427612,"identity":"d7dd190b-4b49-46a6-9168-87cfa08c16df","order_by":1,"name":"Cokorda Bagus Ghana Indra Pradana","email":"","orcid":"https://orcid.org/0009-0005-6799-1149","institution":"Department of Economics, Faculty of Economics and Business, Universitas Gadjah Mada, Yogyakarta, Indonesia","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Cokorda","middleName":"Bagus Ghana Indra","lastName":"Pradana","suffix":""},{"id":280427613,"identity":"5dbf5b16-e228-4296-884e-05541e0a2edd","order_by":2,"name":"Catur Sugiyanto","email":"","orcid":"","institution":"Department of Economics, Faculty of Economics and Business, Universitas Gadjah Mada, Yogyakarta, Indonesia","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Catur","middleName":"","lastName":"Sugiyanto","suffix":""}],"badges":[],"createdAt":"2024-03-17 03:45:58","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false,"coiExplicitlySet":false},"doi":"10.21203/rs.3.rs-4115318/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4115318/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":52891644,"identity":"5bb68abd-925c-4c95-944a-109f64269fea","added_by":"auto","created_at":"2024-03-18 11:42:32","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":124684,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGraph 1. Scatter Plot of HIEF and Population Growth\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4115318/v1/ec66ca707f006d5f8746434c.png"},{"id":52891645,"identity":"9fed5fbc-9992-432e-ad8b-8022fb6a57af","added_by":"auto","created_at":"2024-03-18 11:42:32","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":449693,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGraph 2. Scatter Plot of HIEF and Income Growth\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4115318/v1/1080670a63b064ff8cf57060.jpeg"},{"id":52891899,"identity":"8d82f8ba-2013-4e9a-af32-58a8df0d4842","added_by":"auto","created_at":"2024-03-18 11:50:34","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":891052,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4115318/v1/d14d3a94-5c66-4bcb-871d-5acff54b7213.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eAnalysing the Link between Population Diversity, Population Growth, and Income\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe world\u0026rsquo;s population is expected to increase by 2\u0026nbsp;billion, from 7.7\u0026nbsp;billion to 9.7\u0026nbsp;billion, by 2050 and reach a peak close to 11\u0026nbsp;billion at the end of the century as the world battles with declining fertility rates (United Nations, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The global fertility rate is expected to fall from 2.5 in 2019 to 1.9 births per woman by the year 2100 and the global median age is also projected to rise from 31 to 42 in the same period (Cilluffo \u0026amp; Ruiz, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The relationship between demographic parameters, such as population and fertility, is a complex and multifaceted topic that has been the subject of much research and debate. Fertility, or the birth of children per woman, is influenced by a wide range of factors, including biological, social, economic, and environmental factors (Bao, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). At the same time, demographic change which studies how human population changes over time is driven by a combination of fertility rates, mortality rates, age profile of the population, and migration patterns (Pew Research Center, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Ranganathan, Swain, \u0026amp; Sumpter, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite the importance of understanding the impact of diversity on societal dynamics, there is a surprising lack of research specifically examining how the racial and ethnic diversity of a population may influence its growth. This is of great significance as a population with a variety of ethnic groups can result in strategic interactions that promote pronatalism and increase fertility rates, as leaders of these groups encourage policies that boost fertility and population (Papyrakis \u0026amp; Mo, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). The motivation to further examine this topic also originates from observing Japan with declining population growth and having one of the most homogeneous populations even among advanced economies. Japan\u0026rsquo;s population has been dwindling mainly due to falling fertility rate, which ranged at 1.3 for the 2019\u0026mdash;2021 period, while the ideal replacement fertility rate or the number of children a woman needs to have for the population to sustain itself is 2.1 children for every woman (OECD, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). At the same time, this population problem may be exacerbated by the fact that Japan is ethnically homogeneous. The Japanese population comprises 97.8% of Japan\u0026rsquo;s total population making it one of the most ethnically homogeneous country among advanced economies (Statistics Bureau of Japan, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Conversely, countries with higher fertility rates, such as India and Indonesia, tend to be more ethnically heterogeneous. Both countries have a fertility rate of 2.03 and 2.17 respectively in 2021 which are still relatively close to the ideal replacement fertility rate while having a large varying ethnicity number (OECD, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). India alone is a highly diverse country with over 2,000 ethnic groups representing each of the world\u0026rsquo;s major religions (Statista, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The majority of these ethnic groups in India are Indo-Aryan and Dravidian, constituting 72% and 25% of India's total population, respectively, while other ethnic groups account for 3% of the total population (Central Intelligence Agency, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Similarly, the Indonesian population is also incredibly diverse, comprising over 1330 ethnic groups, with the two largest being the Javanese, who make up 40.05% of the total population, and the Sundanese, who make up 15.5%, while the proportion of the remaining ethnic groups are less than 5 percent each (Statistics Indonesia, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). These facts underline the possible connection between a given country\u0026rsquo;s diversity and its population growth, highlighting the need for further research into potential relationship between the aforementioned issues and how it affects economic outcome.\u003c/p\u003e \u003cp\u003ePrevious discussion on fertility has ushered in a new era that brings a different demographic implication as some of these initially stylized facts are no longer universally relevant. The first-generation empirical modelling for fertility were made to account for two regularities that has held for many decades across nations and within families in a particular country i.e., a negative relationship between income and fertility as well as a negative relationship between women\u0026rsquo;s labour force participation and fertility (Doepke, Hannusch, Kindermann, \u0026amp; Tertilt, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Such trade-offs relate heavily to the quantity-quality trade-off theory of Becker \u0026amp; Lewis (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1973\u003c/span\u003e) that a smaller family size allows for more resources to be allocated to each child which improves the overall child quality within a family given the limited resources available, therefore implying that a decrease in fertility would encourage more human capital investment for every child (Wang \u0026amp; Zhang, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Lately, however, such consensus in said quantity-quality trade-offs mentioned beforehand has been undergoing a major shift. Across the high-income world, some evidence of the positive relationship between fertility and income has been observed with shifting key determinants of fertility choice mainly due to changing family policy and social norms, the trend of accommodating fathers, as well as flexible labour markets (Doepke et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMeanwhile, the topics of racial or ethnic diversity and demographic have also gathered much attention in recent times. By 2050, it is estimated that half of the world\u0026rsquo;s population growth mostly originates from Asian and African countries such as India, Nigeria, Pakistan, the Democratic Republic of the Congo, Ethiopia, Tanzania, Indonesia, Egypt, and the United States of America (in descending order of growth) (United Nations, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) with one in four of the total global population having Sub-Saharan Africa origin by that same period (Suzuki, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). India has overtaken China in terms of population number in 2023, becoming the world\u0026rsquo;s most populous country, and both countries face divergent demographic future with China suffering from declining populations due to falling fertility rates and India\u0026rsquo;s population is still set to continue growing (United Nations, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2019\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Thus, it is projected that in 2050 the 5 most populous countries are India, China, United States of America (USA), Nigeria, and Pakistan (United Nations, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Various high-income countries, such as the United States, are also trending towards a more diverse population group. The white non-Hispanic will account for 47% of the total US population by 2050 while the rest consists of a mix of Hispanic/Latinos, black, and Asian populations signalling a trend towards what is referred to as \u0026ldquo;minority whites\u0026rdquo; in the US (Frey, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Passel \u0026amp; Cohn, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe discussion on diversity is primarily influenced by two contrasting views in which one perspective portrays diversity as a catalyst for growth while the other suggests it hinders growth (Rodr\u0026iacute;guez-Pose \u0026amp; von Berlepsch, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). These contrasting perspectives indicate that the approaches to assess the relationship between population diversity and growth are not so straightforward. Several existing studies have shown how diversity has demographic and economic implications. G\u0026ouml;ren (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) showed how ethnic diversity affects economic growth of 100 countries from the 1960\u0026mdash;1999 period. The study found that ethnic diversity led to higher fertility rate and indirectly contributed to international trade positively that proved beneficial in rejuvenating declining populations (G\u0026ouml;ren, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Collier (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2001\u003c/span\u003e) found that countries characterized by dominance, where one group becomes the majority, have worse economic performance than fractionalized countries, where there are many ethnic groups. For instances, China\u0026rsquo;s efforts to improve income and education across all ethnic groups still causes income and educational gap to persists among the non-Han ethnic minorities in China or even grew over time (Chia \u0026amp; Hruschka, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), but simply comparing the Han and non-Han does not paint a full picture in the experience of each minority group. One minority group which is the Man tends to have an overall higher income and education level than the Han, the Buyi have equivalent educational achievement with the Han, while the Miao and Tujia have lower overall achievement than the Han (Chia \u0026amp; Hruschka, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Additionally, fractionalized societies also face poorer public sector performance than homogeneous societies (Collier, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Ratna et al. (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) analyzed the effect of diversity by measuring both racial and linguistic diversity and found mixed results i.e., racial diversity negatively affects Gross State Product (GSP) growth, linguistic diversity positively affects GSP growth.\u003c/p\u003e \u003cp\u003eOn a similar note, there have been mixed results on how countries with varying income levels are affected by population changes. Montalvo \u0026amp; Reynal-Querol (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2005\u003c/span\u003e) found that social polarization, which is the segregation of social groups due to economic factors such as income inequality and social displacement, negatively affects economic growth through the reduction in investment as well as an increase in public consumption and civil wars incidence. Another study by Peterson (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) noted that rapid population growth in low-income countries can result in a demographic dividend in the long run as these youths grow to be productive adults. However, the study also noted that growth induced by high fertility rates commonly found in low-income countries reduce overall well-being, while growth induced by decreased mortality rates is viewed more favorably resulting in higher positive impact on savings and economic growth. High-income countries often experience low or negative population growth, which can lead to an ageing population. Higher population growth would alleviate the pressure on the working-age population and the government to support the elderly. However, this is unlikely to happen as fertility rates in high-income countries continue to decline (Peterson, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite numerous existing research that has specifically analyzed how diversity causes demographic and economic change, studies that specifically analyze the relationship between population diversity and population growth while incorporating both time-variant and cross-country components are limited. To the best of our knowledge, the majority of existing research trade-off with either focusing on time-varying components that is limited to a narrow period at a given area or research with a cross-country component but is mostly limited to a single or multiple non-continuous time period, such as in the case of Ananta et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), DiRienzo et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), Docquier et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), and Rodr\u0026iacute;guez-Pose \u0026amp; von Berlepsch (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Such analysis could not explain how the relationship between ethnic diversity, population, and income evolves over time and across different countries. Such analysis could not explain how the relationship between ethnic diversity, population, and income evolves over time and across different countries. Understanding this complex relationship would enable policymakers to formulate sound policies that could utilize the benefits of ethnic diversity while also addressing its potential problems.\u003c/p\u003e \u003cp\u003eThis research attempts to fill this gap in the literature by examining how population diversity influences population growth and income. We utilized a panel dataset consisting of 150 countries ranging from 1960\u0026ndash;2013 and analyzed using a dynamic panel regression model, specifically the system Generalized Method of Moments (GMM) method to account for fixed effect and dynamic panel model-specific bias. It also fits in an unbalanced panel data and data that suffers from endogeneity in its variables.\u003c/p\u003e \u003cp\u003eOur results confirmed that ethnically diverse populations and migration contribute to the expansion of the population. It may relate to the openness and acceptance of other ethnicities to migrate and the strategic interaction between ethnic groups to compete for influence, thus promoting pronatalism policies, as indicated by the rising fertility rate in such mixed demographic compositions. However, we also found a negative correlation between population diversity and income growth. The result indicates that while diversity may foster population growth, it may not necessarily lead to income growth.\u003c/p\u003e \u003cp\u003eThis paper is divided into several sections. Section two provides an insight into the literature review. Section three describes the methodology utilized in this research. Section four elaborates on the empirical result and section five concludes this research.\u003c/p\u003e"},{"header":"2. Literature Review","content":"\u003cp\u003eThe discussion on diversity is not a straightforward matter that is often controversial and discussed across a diverse range of disciplines from both natural and social science. The discourse on diversity is dominated by two opposing perspectives with one view depicting diversity as growth-promoting while the other view depicts it as obstructing growth (Rodr\u0026iacute;guez-Pose \u0026amp; von Berlepsch, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Differing perspectives mean the angles in evaluating the link between population diversity and population growth are not uniform, also implying that a variety of parameters as a proxy for diversity are used with a distinct aspect of the notion. The most prevalent proxies for diversity studies include population fractionalization, polarization, and segregation therefore the fact that diversity may either promote or hinder growth depends on the proxy being used (Rodr\u0026iacute;guez-Pose \u0026amp; von Berlepsch, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eLiteratures on how diversity promotes growth highlight the role of innovations and skills as its key determinants. The movement of migrants from to a host country brings along a novel range of skills, knowledge, and perspectives that are beneficial for nurturing technological innovation and positive economic outcomes (Bove \u0026amp; Elia, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). For instance, immigrant diversity is positively correlated with economic prosperity with a one percentage point in skilled migrant diversity increases GDP per capita by 2 percent (Alesina, Harnoss, \u0026amp; Rapoport, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). On a similar note, diversity has also been shown to have positive impact on wages among high-income jobs that demand complex problem-solving skills (Cooke \u0026amp; Kemeny, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) as well as diversity of high-skilled immigrants on economic growth, as confirmed that there is an increase of 6% in GDP per capita for every 10% increase in high-skilled diversity (Docquier et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Similar evidence was also found regarding the positive effect of diversity on GDP per capita but this effect is found to be stronger and more consistent among developing countries (Bove \u0026amp; Elia, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). However, it is necessary to note that diversity has consistently been proven to have no significant effect on economic outcomes for low skilled jobs (Cooke \u0026amp; Kemeny, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Docquier et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Suedekum, Wolf, \u0026amp; Blien, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Production specialization is also found to act as a catalyst for diversity promoting growth in the form of trade. Montalvo \u0026amp; Reynal-Querol (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) highlighted the positive relationship between ethnic diversity and economic growth due to the increase in inter-ethnic groups' trade activities, specifically in smaller regions, as different ethnic groups have different production preferences.\u003c/p\u003e \u003cp\u003eThere is a strong argument against discrimination and non-inclusion in the diversity context as, evidently, the exclusion of a sizable population group comes at the severe cost of demographic change related to an ageing population and the growing proportion of traditionally underprivileged groups in the labour market (OECD, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Aside from the positive economic outcome of diversity, one literature also suggests that ethnic diversity may induce higher fertility rate leading to population growth, mainly due to political factors. A diverse population leads to strategic interactions among ethnic groups, promoting pronatalism and increasing fertility rates as group leaders incentivize fertility-boosting policies (Papyrakis \u0026amp; Mo, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Some evidence also reveals the cost of sustaining non-inclusion of diverse groups. For instance, France could see an increase of around EUR 150\u0026nbsp;billion over 20 years by increasing employment rates of disadvantaged groups to the average level, translating to a 0.35 percent yearly GDP increase; or reducing the labour force participation gender gap by a quarter across the OECD by 2025 may result in 1 percentage point rise in projected baseline GDP growth from 2013-25 while halving the gap could result in an almost 2.5 percentage point increase (OECD, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA common theme among the literature arguing that diversity promotes growth is that the diversity is based on the number of different population groups within an area with variation based on language, religion, and ethnicity. These literatures incline to use a fractionalization index as a measure of population diversity. The idea of a fractionalization index presumes that the greater the number of ethnic groups, the higher the diversity in a society thus positively inducing the potential for the growth of economic outcome (Rodr\u0026iacute;guez-Pose \u0026amp; von Berlepsch, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Unfortunately, these fractionalization indices and preceding literature on diversity usually do not consider the size and distance of different ethnic groups. Additionally, most studies emphasize more on evaluating how diversity affects the outcome within a country or even at an individual level, indicating the lack of studies that incorporate an examination at a wide cross-country level.\u003c/p\u003e \u003cp\u003eThe opposite view that argues diversity inhibits growth considers diverse groups to be the main destabilizing factor with the potential to escalate into a social turmoil or conflict. Literature that suggests diversity inhibits growth includes fractionalization as a proxy for diversity similar to the growth-promoting group but places increasing emphasis on segregation and polarization indices (Rodr\u0026iacute;guez-Pose \u0026amp; von Berlepsch, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The cost of fractionalization on a macroeconomic scale has been empirically ingrained as measured through the ethno-linguistic diversity lens in a study by Easterly \u0026amp; Levine (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1997\u003c/span\u003e) that discovers ethnic fragmentation is associated with lower economic growth, particularly in Africa, mainly due to the frequent ethnic conflict occurring in the region. Consequently, this diversity causes rent-seeking behaviour among different groups that further undermine efforts to adopt sound public policies as well as resulting in poor education attainment, high financial debt, and low infrastructure quality as a result of high segregation levels. G\u0026ouml;ren (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) further highlighted the negative direct consequence of ethnic diversity on economic growth, the indirect negative consequence of ethnic polarization on economic outcome through human capital, investment, trade openness, and civil war, as well as noting that ethnically diverse countries possess a higher average fertility rate.\u003c/p\u003e \u003cp\u003eOne study further examines the effect of diversity by separating between dominance, in which one group becomes the majority, and fractionalization, where there are many ethnic groups. Collier (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2001\u003c/span\u003e) finds that countries characterized by dominance are found to have worse economic performance than fractionalized countries, which are generally non-problematic in democracies but can be damaging in dictatorship. Additionally, fractionalized societies also face poorer public sector performance than homogeneous societies (Collier, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Moreover, Montalvo \u0026amp; Reynal-Querol (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) concludes that social polarization negatively affects economic growth through the reduction in investment, increase in public consumption and civil wars incidence. Meanwhile, Ratna et al. (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) studied the macroeconomic effects of social diversity across 48 states in the United States (US), finding mixed empirical results for the effect of diversity on Gross State Product (GSP) per capita growth while racial diversity decreases GSP growth and linguistic diversity increases GSP growth.\u003c/p\u003e \u003cp\u003eThere are mixed results on how countries with varying income levels are affected by population changes. According to Peterson (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), rapid population growth in low-income countries can lead to short and medium-term challenges due to a larger young population but can result in a demographic dividend in the long run as these youths grow to be productive adults. However, the study also finds that growth induced by high fertility rates commonly found in low-income countries reduce overall well-being, while growth induced by decreased mortality rates is viewed more favorably resulting in higher positive impact on savings and economic growth. In contrast, low or even negative population growth found in high-income countries can result in an ageing population, putting burden on the productive age group and government to support the elderly population (Peterson, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOnce again, there is a common theme among the literature that establishes the fact that diversity inhibits growth. Diversity is emphasized as the cause of the negative consequences of polarization and segregation and separate indices have been used to investigate these consequences from a distinct aspect of diversity altogether. Polarization indices focus more on the size of one group to another and the distance separating them rather than the quantity of groups within a given population. Groups with more distance amongst each other would have more similarity in size and a stronger separation between groups reduce communications which negatively affects economic development due to diversity (Rodr\u0026iacute;guez-Pose \u0026amp; von Berlepsch, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The diverse culture pervasive among different groups affects trust, disturbing the coordination of economic actors and their interaction, as well as enlarging the gap in preferences and giving rise to conflict. Nevertheless, the interaction among diverse groups concurrently generates a myriad of experiences, skills, and knowledge that advances technological innovation and ideas, increase productivity and quality of goods and services, as well as procreation of society (Alesina et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Rodr\u0026iacute;guez-Pose \u0026amp; von Berlepsch, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAligning with most of the previous research, this study will focus on a single dimension, which is ethnic diversity that is measured by the Historical Index of Ethnic Fractionalization (HIEF) (Drazanova, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The HIEF is defined as the probability that two randomly chosen individuals in the same country do not share the same ethnicity. This variable is used to measure the degree of population diversity in a country, which is the main independent variable in this research. This variable is used to measure the degree of population diversity in a country, which is the main independent variable in this research. The dependent variables, namely population growth and income growth, are measured by the population growth and GNI per capita variable that are sourced from the World Bank Dataset. The use of GNI per capita as a proxy to income growth has been previously observed in empirical literature (Janvry \u0026amp; Sadoulet, 2000).\u003c/p\u003e \u003cp\u003eThe control variables in this research, namely population density, fertility rate, mortality rate, age structure, net migration, and sex ratio, are selected by examining earlier literature and theoretical arguments. According to Malthus, from his book titled \u0026ldquo;An Essay on the Principle of Population\u0026rdquo;, higher population size will limit the available resources for each person, which leads to decrease in population growth. Both fertility rate and mortality rate is found to affect economic growth, which is closely related to income growth (Ashraf, Weil, \u0026amp; Wilde, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Zhang, Zhang, \u0026amp; Lee, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Furthermore, Ozgen et al. (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) have established that net migration is positively correlated with per capita income growth. Meanwhile, Imbalanced sex ratio is also found to negatively affect birth rate which leads to decrease in population growth (Hesketh \u0026amp; Xing, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Additionally, an increase in sex ratio at birth that tends to skew the proportion between male and female will significantly reduce economic growth in the short and long-term (Wu, Ali, Zhang, Chen, \u0026amp; Hu, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Moreover, female labour force participation rate has a negative effect on population growth through the reduction in fertility rate, since women that are involved in the labor force tend to delay their childbearing due to the work\u0026rsquo;s demands (Rafique Umar \u0026amp; Shoaib, 2015). On the other hand, an increase in the female labour force participation rate is found to have a positive and significant effect on economic well-being (Tsani, Paroussos, Fragiadakis, Charalambidis, \u0026amp; Capros, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e"},{"header":"3. Methodology","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Data\u003c/h2\u003e \u003cp\u003eThe panel dataset that is utilized in this research consists of 150 countries from 1960\u0026mdash;2013, considering the availability of the latest data from the World Bank Dataset, Historical Index of Ethnic Fractionalization (HIEF) dataset that is derived from the Cline Center for Democracy Composition of Religious and Ethnic Groups (CREG) that is further extended by Drazanova (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) to account for cross country and time-varying effect, and International Labour Organization (ILO). The Historical Index of Ethnic Fractionalization (HIEF) represents the proxy for diversity (\u003cem\u003eEF\u003c/em\u003e\u003csub\u003e\u003cem\u003eit\u003c/em\u003e\u003c/sub\u003e). The index has a ratio between 0 (complete homogeneity) and 1 (complete heterogeneity). The population density (\u003cem\u003ePD\u003c/em\u003e\u003csub\u003e\u003cem\u003eit\u003c/em\u003e\u003c/sub\u003e) is defined as the quantity of people per square kilometre of land area in a given year and period, the fertility rate (\u003cem\u003eFR\u003c/em\u003e\u003csub\u003e\u003cem\u003eit\u003c/em\u003e\u003c/sub\u003e) is represented by the total fertility rate or the total number of births per woman during her childbearing years in a given country and period, mortality rate (\u003cem\u003eMR\u003c/em\u003e\u003csub\u003e\u003cem\u003eit\u003c/em\u003e\u003c/sub\u003e) is represented by the infant mortality rate or the death of an infant before 1 year of age for every 1000 live births in a given country and period, net migration (\u003cem\u003eMig\u003c/em\u003e\u003csub\u003e\u003cem\u003eit\u003c/em\u003e\u003c/sub\u003e) is obtained from the number of immigrants minus the number of emigrants including citizens and noncitizens in a given country and period, the sex ratio (\u003cem\u003eSex\u003c/em\u003e\u003csub\u003e\u003cem\u003eit\u003c/em\u003e\u003c/sub\u003e) utilizes the sex ratio at birth or the ratio of male births per female births on a 5 year average in a given country and period. All the aforementioned data were obtained from the World Development Indicator from the World Bank Database. Finally, the female labour force participation rate (\u003cem\u003eFLC\u003c/em\u003e\u003csub\u003e\u003cem\u003eit\u003c/em\u003e\u003c/sub\u003e) was obtained from a combination of data from the International Labour Organization (ILO) estimates and complemented by the national estimates of respective countries in a given period.\u003c/p\u003e \u003cp\u003eThe countries consist of 49 countries from Africa, 43 from Asia, 38 from Europe, 3 from North America, 4 from Oceania, and 13 from South America. Measuring diversity has proven to be a challenge due to data limitations. On the following note, diversity could be defined in many terms since any person could be categorized into multiple groups, such as gender, age, religion, ethnicity etc. Therefore, the majority of economic analyses about diversity focus on only one dimension (OECD, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and in this research we focus specifically on how ethnic diversity relates to population growth and income.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Empirical Strategy\u003c/h2\u003e \u003cp\u003eIn order to investigate how population diversity may be related with population growth and income growth, the following equation is used to perform the estimation:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$${y}_{it}={\\alpha }_{0}+{\\beta }_{1}{EF}_{it}+{\\beta }_{2}{PD}_{it}+{\\beta }_{3}{FR}_{it}+{\\beta }_{4}{MR}_{it}+{\\beta }_{5}{Mig}_{it}+{\\beta }_{6}{Sex}_{it}+{\\beta }_{7}{FLC}_{it}+{\\vartheta }_{i} +{\\epsilon }_{it}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003e(1)\u003c/p\u003e \u003cp\u003ewhere \u003cem\u003ey\u003c/em\u003e\u003csub\u003e\u003cem\u003eit\u003c/em\u003e\u003c/sub\u003e refers to both the population growth (Model A) and gross national income per capita (Model B) as the dependent variables in country \u003cem\u003ei\u003c/em\u003e and year \u003cem\u003et\u003c/em\u003e. Notation \u003cem\u003eEF\u003c/em\u003e\u003csub\u003e\u003cem\u003eit\u003c/em\u003e\u003c/sub\u003e is the independent variable that refers to the HIEF. Meanwhile, \u003cem\u003ePD\u003c/em\u003e\u003csub\u003e\u003cem\u003eit\u003c/em\u003e\u003c/sub\u003e, \u003cem\u003eFR\u003c/em\u003e\u003csub\u003e\u003cem\u003eit\u003c/em\u003e\u003c/sub\u003e, \u003cem\u003eMR\u003c/em\u003e\u003csub\u003e\u003cem\u003eit\u003c/em\u003e\u003c/sub\u003e, \u003cem\u003eMig\u003c/em\u003e\u003csub\u003e\u003cem\u003eit\u003c/em\u003e\u003c/sub\u003e, \u003cem\u003eSex\u003c/em\u003e\u003csub\u003e\u003cem\u003eit\u003c/em\u003e\u003c/sub\u003e, and \u003cem\u003eFLC\u003c/em\u003e\u003csub\u003e\u003cem\u003eit\u003c/em\u003e\u003c/sub\u003e are a set of control variables that consist of population density, fertility rate, mortality rate, net migrations, sex ratio, and female labour force participation respectively. Finally, \u0026#120599;\u003csub\u003ei\u003c/sub\u003e and \u003cem\u003eε\u003c/em\u003e\u003csub\u003e\u003cem\u003eit\u003c/em\u003e\u003c/sub\u003e are the country-specific effect and error term. Among the data, some adjustments are necessary to allow a proper estimation for the model by transforming to natural logarithm. These consist of the net migrations (\u003cem\u003eMig\u003c/em\u003e\u003csub\u003e\u003cem\u003eit\u003c/em\u003e\u003c/sub\u003e) data, the gross national income data, and the population density (\u003cem\u003ePD\u003c/em\u003e\u003csub\u003e\u003cem\u003eit\u003c/em\u003e\u003c/sub\u003e) data.\u003c/p\u003e \u003cp\u003eTo perform the estimation above, the dynamic panel regression method is chosen. This decision is made by considering the two following issues as stated by OECD (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). First, the issue of unobserved heterogeneity could affect both the outcome variable and ethnic diversity and can lead to bias in the estimated effects of diversity (Alesina \u0026amp; Ferrara, 2005). Second, there is a limited amount of research that has established the causal relationship between diversity and economic outcomes by utilizing the instrumental variables (IV) estimation.\u003c/p\u003e \u003cp\u003eThe dynamic panel regression method, which allows the use of the lag value of the variable in the model, is capable in overcoming issues in the cross-sectional type model that arise from the country-specific and time-specific unobserved variables that lead to omitted variable bias and endogeneity problem (Levine, Loayza, \u0026amp; Beck, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). Among the various dynamic panel regression methods, Generalized Method of Moments (GMM) method is found to be able to tackle various issues in model estimation, such as fixed effect, endogeneity, and dynamic panel model-specific bias. The flexibility of this method enables it to be used in an unbalanced panel data and data that suffers from endogeneity in its variables. The capability to tackle various issues and estimation problems leads to the widespread use of GMM, mainly difference GMM and system GMM in empirical literature (Rahman, Rana, \u0026amp; Barua, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Roodman, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2009\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis research specifically prefers using the system Generalized Method of Moments (GMM) over the difference GMM for conducting model estimation. The system GMM method allows for estimation in both first difference and level forms, whereas the difference GMM method only utilizes the first-difference form for its estimation. This distinction in characteristics results in higher precision, efficiency, and lower bias from the system GMM approach compared to the difference GMM method, particularly when dealing with small panel data (Soto, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). This observation aligns with the findings of Bond (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2002\u003c/span\u003e) who concludes that the difference GMM method is more susceptible to finite sample bias than the system GMM method.\u003c/p\u003e \u003cp\u003eThese limitations have led to a greater preference in the empirical literature for using the system GMM approach over the difference GMM. For instance, Levine et al. (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2000\u003c/span\u003e), Rahman et al. (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), and Zarra-Nezhad et al. (\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) have opted for the system GMM method for model estimation after comparing it to the difference GMM method in order to mitigate potential issues in their research. The preference for using the system GMM approach is also evident in literature discussing similar topics. Choudhury \u0026amp; Sahu (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), in their examination of the role of ethnic fragmentation on the relationship between fiscal decentralization and government size, employ the system GMM method as one of their research techniques. Additionally, Ajide et al. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), who investigate the mediating role of institutions in the nexus between ethnic diversity and inequality, also utilize the system GMM method alongside pooled OLS and fixed effects methods.\u003c/p\u003e \u003cp\u003eIn ensuring the robustness of our model, we introduce an additional variable which categorizes countries based on income level, following the World Bank historical classifications by income as of 2013 according to the latest available period in our dataset. The equation is as follows:\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$${y}_{it}={\\alpha }_{0}+{\\beta }_{1}{EF}_{it}+{\\beta }_{2}{PD}_{it}+{\\beta }_{3}{FR}_{it}+{\\beta }_{4}{MR}_{it}+{\\beta }_{5}{Mig}_{it}+{\\beta }_{6}{Sex}_{it}+{\\beta }_{7}{FLC}_{it}+{\\beta }_{8}{IC}_{i}+ {\\vartheta }_{i} +{\\epsilon }_{it}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cem\u003ey\u003c/em\u003e\u003csub\u003e\u003cem\u003eit\u003c/em\u003e\u003c/sub\u003e refers to the population growth (Model C) and gross national income per capita (Model D) as the dependent variables in country \u003cem\u003ei\u003c/em\u003e and year \u003cem\u003et\u003c/em\u003e. The additional categorical variable to indicate country\u0026rsquo;s income class is represented with ICi. This variable also provides a clearer view of understanding the relationship between diversity, population growth, and income growth by factoring in the country\u0026rsquo;s income level.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Results and Discussions","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Descriptive Statistics\u003c/h2\u003e \u003cp\u003eA closer look at the data shows that both South Korea and North Korea have the lowest Historical Index of Ethnic Fractionalization (HIEF) value, measuring at 0 in the 1960s. Even in the latest available data of 2013, both countries still had relatively low HIEF values at 0.095 for South Korea and 0.02 for North Korea. Meanwhile, African countries are found to be highly diverse in terms of ethnic groups, such as Liberia, Uganda, and Togo, with HIEF values measuring at 0,89, 0,88, and 0,87 respectively. The complete list of countries along with their HIEF rankings at the earliest and latest available year are available at the \u003cspan refid=\"Sec10\" class=\"InternalRef\"\u003eAppendix\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive Statistics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eObs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStd. Dev.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMax\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePopulation Growth\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8,108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.909\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.770\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-27.722\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e19.360\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGNI per Capita\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3,526\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9805.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14023.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e189.518\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e86012.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHIEF\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7,287\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.440\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.270\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLog Population Density\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6,150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.848\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.389\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.098\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.940\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFertility Rate\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8,262\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.215\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.078\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMortality Rate\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7,479\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56.984\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e47.040\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e228.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLog Migration\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8,262\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14.582\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.185\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e15.209\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex Ratio\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8,262\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.178\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFemale Labor Participation Rate\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4,060\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48.509\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16.066\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e93.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFurther inspection based on scatter plots to examine the association between HIEF, population growth, and GNI per capita shows a tendency for population growth to be higher in ethnically diverse populations, adjusting for outliers. Meanwhile, higher GNI per capita is observed more in lower diversity settings. These results signify the potential of a positive correlation between HIEF and population growth and a negative correlation between HIEF and income growth.\u003c/p\u003e \u003cp\u003e \u003cb\u003eGraph 1. Scatter Plot of HIEF and Population Growth\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eGraph 2. Scatter Plot of HIEF and Income Growth\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Regression Results\u003c/h2\u003e \u003cp\u003eBased on the baseline results in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e below, population diversity represented by the HIEF is positive and statistically significant at 1% to population growth. In model A, the fertility rate and net migration are positively correlated to population growth while the mortality rate is negatively correlated to population growth. All three of the previously mentioned control variables are statistically significant at the 1% level. Conversely, population density and sex ratio show no significant relationship to population growth. On a similar note, population diversity also shows a statistical significance at 1% level but negative relationship to income growth. In model B, population density, mortality rate, and sex ratio are negatively correlated with income growth at the 5%, 1%, and 5% significance level respectively. Fertility rate and net migration in model B do not show any significant relationship to income growth. Additionally, female labour force participation has also been shown to be statistically significant at 5% and having an inverse relationship with population growth in model A while showing no relationship at all with income growth in model B.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSystem GMM Baseline Estimation Results\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDependent: Population Growth\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDependent: Income Growth\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiversity (HIEF)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.0661***\u003c/p\u003e \u003cp\u003e(0.7959)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-2.0308***\u003c/p\u003e \u003cp\u003e(0.56511)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLog Population Density\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.1818\u003c/p\u003e \u003cp\u003e(0.1750)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e-0.2188**\u003c/b\u003e\u003c/p\u003e \u003cp\u003e(0.1035)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFertility Rate\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.8115***\u003c/b\u003e\u003c/p\u003e \u003cp\u003e(0.1815)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.1747\u003c/p\u003e \u003cp\u003e(0.1504)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMortality Rate\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e-0.0259***\u003c/b\u003e\u003c/p\u003e \u003cp\u003e(0.0085)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e-0..0301***\u003c/b\u003e\u003c/p\u003e \u003cp\u003e(0.0079)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLog Net Migration\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e3.0876***\u003c/b\u003e\u003c/p\u003e \u003cp\u003e(1.1253)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1849\u003c/p\u003e \u003cp\u003e(0.3058)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex Ratio\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-7.1887\u003c/p\u003e \u003cp\u003e(9.0649)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e-12.7315**\u003c/b\u003e\u003c/p\u003e \u003cp\u003e(5.0046)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFemale Labor Participation Rate\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e-0.0232\u003c/b\u003e**\u003c/p\u003e \u003cp\u003e(0.0097)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0042\u003c/p\u003e \u003cp\u003e(0.0084)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eConstants\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e-38.1278\u003c/b\u003e**\u003c/p\u003e \u003cp\u003e(17.9830)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e22.1870***\u003c/b\u003e\u003c/p\u003e \u003cp\u003e(7.1313)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eObservations\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3946\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2564\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCountries\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e127\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eNotes: Standard errors are shown in parentheses. ***, **, and * show significant level of 1%, 5%, and 10% respectively.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe main findings indicate that ethnic diversity is statistically significant on both population growth and income growth. Diversity has a positive correlation with population growth and a negative correlation with income growth. The positive correlation of diversity with population growth aligns with G\u0026ouml;ren (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) which concludes that diversity leads to higher population growth through fertility rates. Papyrakis \u0026amp; Mo (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) provides an explanation for this phenomenon that a more diverse population could foster strategic interaction among ethnic groups to compete for influence within the society. To gain more influence, ethnic group leaders may promote pronatalism policy to increase the number of population within the ethnic group, thus elevating their position and dominance in the society. As a result, this will enhance the fertility rate and end up increasing the population growth in the highly diverse society. Similar explanation is also pointed out by Janus (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) who argues that ethnic groups may promote higher fertility rate to increase their voting power relative to other groups. Janus (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) also further specifies that weak political institutions are the key factor in the emergence of this condition, using fertility rates as the key to increase ethnic political power.\u003c/p\u003e \u003cp\u003eThe negative correlation found in income growth is supporting the view that diversity inhibits economic development. The results are in line with Easterly \u0026amp; Levine (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1997\u003c/span\u003e) who also identified a negative association between ethnic fragmentation and economic growth due to the frequent ethnic conflict occurring in the highly diverse region. Diverse society is prone to exhibit a propensity for rent-seeking behaviour, which hinders the effective formulation and implementation of sound public policies. This can lead to adverse consequences, such as poor education attainment, high financial debt, and low infrastructure quality, due to heightened levels of societal segregation. G\u0026ouml;ren (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) also elucidated the adverse direct impact of ethnic diversity on economic growth and the indirect repercussions of ethnic polarization on economic outcomes through four channels, namely human capital accumulation, investment levels, trade openness, and the proclivity towards civil conflict.\u003c/p\u003e \u003cp\u003eIn G\u0026ouml;ren (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), it was stated that education, as one form of human capital accumulation, may not be properly and fairly distributed in an ethnically diverse environment due to the government\u0026rsquo;s intention of using education as a tool to control and influence particular ethnic groups. This situation may lead to lower schooling levels which negatively affects human capital and income growth. Easterly \u0026amp; Levine (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1997\u003c/span\u003e) also noted that diverse societies may be less satisfied with the quality of education due to the disagreements between ethnic groups on the characteristics and aspects of the education itself, such as the language used and the learning materials which could lead up to less investment in human capital. Ogbu \u0026amp; Simons (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e1998\u003c/span\u003e) further pointed out that minority groups are more likely to become suspicious of the public schools that are considered to favor the ruling ethnic group and discriminate against the minorities, thus discouraging them to take on schooling.\u003c/p\u003e \u003cp\u003eThe next channel, level of investment, has been partially explained by Easterly \u0026amp; Levine (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1997\u003c/span\u003e) in the previous discussion. Countries with highly diverse populations are prone to rent-seeking behaviour by each ethnic group. These rent-seeking activities may generate conflict of interest and lead to a problem in reaching an agreement on the kind of public goods that will be provided to the society due to the disharmony between ethnic groups. As a result, this will hinder the development of public infrastructure, education institutions, healthcare, and government policy. This disruption would reduce the level of investment in the productive sector, which will weaken the economic growth and income growth. Ethnic diversity could also affect the economy through free trade channels. Regions with higher ethnic diversity are found to have lower quality of exported goods than the lower ethnic diversity regions due to the difficulties in communicating and collaborating between ethnic groups to produce high quality differentiated products (Luong, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Lower quality of exported goods will weaken the export sector and lead to lower income from export activities. Another channel, which is civil war, has also been identified to hamper economic development and tends to happen in ethnically diverse countries. According to Collier (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2001\u003c/span\u003e), civil war could rapidly escalate and cause human and physical capital destruction and also mass exodus of the educated population. The consequences of this would severely inhibit the country\u0026rsquo;s human development and the economy as the country is unable to function properly.\u003c/p\u003e \u003cp\u003eFurthermore, an increased level of ethnic diversity can lead to fierce competition for jobs among different ethnic groups. In an ideal scenario, this heightened competition should act as a filter for employers to recruit the most competent applicants. As a result, this competitive environment can be beneficial for highly skilled workers. However, those who are unsuccessful in this competition and have already relocated to these regions may find themselves settling for lower-tier jobs, which subsequently leads to lower earnings according to the statistical discrimination theories (Horvath \u0026amp; Huber, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Additionally, DiRienzo et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) found that countries with higher ethnic diversity tend to be less competitive. Consequently, lower competitiveness means having lower productivity and this causes a country\u0026rsquo;s likelihood of sustained growth to be lower than more competitive countries, also causing the quality of labour to also be less competitive.\u003c/p\u003e \u003cp\u003eBased on the estimation result, another interesting point should be highlighted. Previous discussion has stated that ethnic diversity can have a positive or negative effect on the economy depending on the variable that is used as a measure (Rodr\u0026iacute;guez-Pose \u0026amp; von Berlepsch, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Empirically, ethnic fractionalization measure is generally related to higher economic growth, while ethnic polarization measure is frequently related to lower economic growth (Ananta et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The results of our estimation that shows a negative correlation between ethnic diversity, as measured by ethnic fractionalization index, and economic growth do not support the general conclusions that are found in the literature.\u003c/p\u003e \u003cp\u003eThe baseline estimation results above do not describe the full picture as it only shows how population growth and income per capita growth (GNI per capita) is explained by population diversity and other control variables at a global scale. To obtain a more accurate description of the aforementioned condition, we show how population diversity relates with population growth and income per capita growth by categorizing it based on the World Bank historical classifications by income as of 2013, following the latest available data for this research.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSystem GMM Estimation Results with Income Level Classification\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDependent: Population Growth\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDependent: Income Growth\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiversity (HIEF)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e2.4310\u003c/b\u003e***\u003c/p\u003e \u003cp\u003e(0.8265)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e-0.8350\u003c/b\u003e**\u003c/p\u003e \u003cp\u003e(0.3960)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLog Population Density\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.2108\u003c/p\u003e \u003cp\u003e(0.1620)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e-0.0929\u003c/b\u003e**\u003c/p\u003e \u003cp\u003e(0.0444)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFertility Rate\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.8962***\u003c/b\u003e\u003c/p\u003e \u003cp\u003e(0.1712)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.0684\u003c/p\u003e \u003cp\u003e(0.0881)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMortality Rate\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e-0.0180**\u003c/b\u003e\u003c/p\u003e \u003cp\u003e(0.0073)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e-0.0081**\u003c/b\u003e\u003c/p\u003e \u003cp\u003e(0.0041)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLog Net Migration\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e2.8950***\u003c/b\u003e\u003c/p\u003e \u003cp\u003e(1.0204)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1345\u003c/p\u003e \u003cp\u003e(0.1253)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex Ratio\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-8.9130\u003c/p\u003e \u003cp\u003e(8.8632)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e-12.5981\u003c/b\u003e***\u003c/p\u003e \u003cp\u003e(3.2192)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFemale Labour Participation Rate\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e-0.0183\u003c/b\u003e**\u003c/p\u003e \u003cp\u003e(0.0083)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.0148\u003c/b\u003e**\u003c/p\u003e \u003cp\u003e(0.0061)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInteraction Variable: Middle-Income to Low-Income Countries\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.8684*\u003c/p\u003e \u003cp\u003e(0.4796)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1.3814***\u003c/b\u003e\u003c/p\u003e \u003cp\u003e(0.3566)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInteraction Variable: High-Income to Low-Income Countries\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e1.6536***\u003c/b\u003e\u003c/p\u003e \u003cp\u003e(0.5497)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e3.0056***\u003c/b\u003e\u003c/p\u003e \u003cp\u003e(0.3543)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eConstants\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e-17.6425**\u003c/b\u003e\u003c/p\u003e \u003cp\u003e(6.5861)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e14.0091\u003c/b\u003e**\u003c/p\u003e \u003cp\u003e(5.3010)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eObservations\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e778\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e471\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCountries\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e127\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eNotes: Standard errors are shown in parentheses. ***, **, and * show significant level of 1%, 5%, and 10% respectively.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e above shows the relationship between population diversity and population growth as well as population diversity and income growth with the addition of a categorical variable based on countries income level, which also acts as a robustness measure of our baseline estimation. With the addition of a categorical variable, the results in model C illustrate that population diversity is statistically significant to both population growth and income growth which is consistent with the previous baseline estimation result. Other independent variables in model C consisting of fertility rate, net migration, as well as the high-income categorical variable are positive and statistically significant towards population growth while mortality rate and female labour force participation are negative and statistically significant towards population growth as the dependent variable. Conversely, population density, sex ratio, and middle-income categorical variable are shown to not have any significant relationship with population growth. On the other hand, the results in model D show that population density, mortality rate, and sex ratio show a negatively significant relationship with income growth as the dependent variable while female labour force participation, middle-income, and high-income categorical variable are positively significant towards income growth. Fertility rate and net migration are the independent variables that are not statistically significant towards income growth as the dependent variable.\u003c/p\u003e \u003cp\u003eOur estimation that involves the income class categorical variable highlights the importance of the significant relationship between diversity and population growth as this particular situation has been plaguing high-income economies, which may potentially cause social and economic problems if left alone (Peterson, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Model C in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows a positive significant relationship between diversity and population growth at the 1% level. At the same time, fertility rate, mortality rate, and net migration respectively are all showing statistical significance towards population growth. Fertility rate and net migration exhibit positive relationships towards population growth. It is also worth noting that female labour force participation causes a positive income growth and this relationship is statistically significant at the 5% level.\u003c/p\u003e \u003cp\u003eThe estimation results also reveal a consensus across countries at all income levels that net migration is correlated with a positive relationship towards population growth. On the other hand, it has been proven that the historical decline in world population due to falling fertility rates occurred in response to higher levels of economic development (Murdoch, Chu, Stewart-Oaten, \u0026amp; Wilber, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In general, the high population growth often found in low-income economies and the low population growth in high-income economies are likely to cause social and economic inequalities as well as inhibit development efforts (Peterson, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). While international migration may help in adjusting these imbalances, such policies are often opposed by many and quite unpopular (Peterson, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The primary reason for the unpopular view of migration is, among others, due to the perceived low labour quality of migrants, political, and sociocultural differences. However, such views may not always reflect the actual migrants\u0026rsquo; economic contributions. In fact, the perceived negative effects of immigrants are often baseless and create a dilemma as most migrants\u0026rsquo; destination countries could benefit with more human capital and expertise brought by immigrants (OECD/ILO, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Therefore, increased efforts to improve the overall well-being of less wealthy populations across the world are vital to solving the dilemma between the perceived low labour quality of migrants and plummeting population of a country (Murdoch et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; OECD/ILO, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Additionally, asylum process claims which are commonly faced by refugee migrants, who are most consistently considered as low labour quality on arrival, should be kept short as this has a strong impact on their future labour outcomes and facilitating them to join the labour market at the earliest possible stage helps to minimize skill losses and increases the effectiveness of human capital investment (Brell, Dustmann, \u0026amp; Preston, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This is particularly relevant in light of G\u0026ouml;ren\u0026rsquo;s (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) findings as prolonged asylum processes may exacerbate disparities in human capital accumulation through education in ethnically diverse environments, leading to an inequitable distribution of resources due to government policies targeting specific ethnic groups.\u003c/p\u003e \u003cp\u003eWe also found that female labour force participation is statistically significant and positive towards income growth implying that there has indeed been a shift in paradigm of how people in high-income countries think about posterity and labour market conditions. Initial fertility models in the past decades across many countries were developed to sufficiently explain two consistent trends: lower fertility rates mean higher income and higher women's workforce participation (Doepke et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). However, our finding on female labour force participation indicate that these facts seem to be changing in recent times as some observation by Doepke et al. (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) has confirmed the positive relationship between fertility and income, implying that women are more active in the workforce while still maintaining the same or even achieve higher level of income. Furthermore, such trends are also supported by flexible labour market conditions with favorable family policies, especially towards women, and changing social norms with fathers caring for their children.\u003c/p\u003e \u003cp\u003ePolicymakers should consider the effects of population diversity on population growth and income growth when designing and implementing policies that affect these outcomes. Adopting a dynamic and context-specific approach to those three aspects is also important as these factors may vary over time and across countries. For example, policies that aim to expand the population of advanced economies or reduce the population growth of developing economies may need to account for the different preferences, behaviours, and incentives of diverse ethnic groups in society. It is also worth pointing out that policies may work well only in certain countries or certain time periods which further reinforce the need for policymakers to assess and adjust their policies accordingly. Additionally, policymakers\u0026rsquo; awareness should also be raised regarding the potential challenges and opportunities that population diversity brings to social cohesion, political stability, and economic development. For instance, policies that promote interethnic cooperation, integration, inclusion, and equitable distribution of income may help to mitigate the negative effects of ethnic conflict, rent-seeking, and policy inefficiencies in highly diverse settings. Meanwhile, policies that foster ethnic diversity, recognition, and representation may help to enhance the positive effects of cultural diversity, innovation, and creativity in society.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eOur research sheds light on the relationship between population diversity and population growth with an additional focus on the relationship between population diversity and income. The dataset spans from 1960\u0026ndash;2013 and includes 150 countries: 49 from Africa, 43 from Asia, 38 from Europe, 3 from North America, 4 from Oceania, and 13 from South America. We confirmed that ethnically diverse populations and migration contribute to the expansion of the population. It may relate to the consensus that regions with diverse ethnic populations are known for their open social dynamics, making them pleasant places to reside and drawing new ethnicities to move in. Diverse populations could also be associated with an increase in strategic interaction between ethnic groups to compete for influence, thus promoting pronatalism policies, which is indicative of a heightened fertility rate within such varied demographic compositions. However, we also found a negative correlation between population diversity and income growth. This can be explained due to the adverse direct impacts of ethnic diversity on economic growth through various potential channels and the correlation between ethnic diversity, lower competitiveness and productivity, which in turn may reduce a country's potential for sustained growth and labour quality. The result indicates that while diversity may foster population growth, it may not necessarily lead to income growth. It is worth pointing out that this study only used HIEF as the proxy variable for ethnic diversity. Therefore, the results may not accurately capture the full extent of the correlation between ethnic diversity, population growth, and income growth.\u003c/p\u003e"},{"header":"Declarations","content":" \u003cp\u003eThe authors are grateful to a colleague for helpful comments and assistance. The paper does not necessarily reflect the opinions of those that have offered assistance or any organization, and responsibility for any errors or omissions rests solely with the authors. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAjide, K. B., Alimi, O. Y., \u0026amp; Asongu, S. A. (2019). Ethnic Diversity and Inequality in Sub-Saharan Africa: Do Institutions Reduce the Noise? \u003cem\u003eSocial Indicators Research\u003c/em\u003e, \u003cem\u003e145\u003c/em\u003e(3), 1033\u0026ndash;1062. https://doi.org/10.1007/s11205-019-02122-y\u003c/li\u003e\n\u003cli\u003eAlesina, A., \u0026amp; Ferrara, E. La. (2005). 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Growing at a slower pace, world population is expected to reach 9.7 billion in 2050 and could peak at nearly 11 billion around 2100. Retrieved 6 September 2023, from United Nations Department of Economic and Social Affairs website: https://www.un.org/development/desa/en/news/population/world-population-prospects-2019.html\u003c/li\u003e\n\u003cli\u003eUnited Nations. (2020). Shifting Demographics. Retrieved 5 August 2023, from https://www.un.org/en/un75/shifting-demographics\u003c/li\u003e\n\u003cli\u003eUnited Nations. (2022). \u003cem\u003eWorld Population Prospects 2022: Summary of Results\u003c/em\u003e. Retrieved from https://www.un.org/development/desa/pd/sites/www.un.org.development.desa.pd/files/wpp2022_summary_of_results.pdf\u003c/li\u003e\n\u003cli\u003eUnited Nations. (2023, April 24). UN DESA Policy Brief No. 153: India overtakes China as the world\u0026rsquo;s most populous country. Retrieved 6 September 2023, from United Nations Department of Economic and Social Affairs website: https://www.un.org/development/desa/dpad/publication/un-desa-policy-brief-no-153-india-overtakes-china-as-the-worlds-most-populous-country/\u003c/li\u003e\n\u003cli\u003eWang, X., \u0026amp; Zhang, J. (2018). Beyond the Quantity\u0026ndash;Quality tradeoff: Population control policy and human capital investment. \u003cem\u003eJournal of Development Economics\u003c/em\u003e, \u003cem\u003e135\u003c/em\u003e, 222\u0026ndash;234. https://doi.org/https://doi.org/10.1016/j.jdeveco.2018.04.007\u003c/li\u003e\n\u003cli\u003eWu, X., Ali, A., Zhang, T., Chen, J., \u0026amp; Hu, W. (2022). An empirical analysis of the impact of gender inequality and sex ratios at birth on China\u0026rsquo;s economic growth. \u003cem\u003eFrontiers in Psychology\u003c/em\u003e, \u003cem\u003e13\u003c/em\u003e. https://doi.org/10.3389/fpsyg.2022.1003467\u003c/li\u003e\n\u003cli\u003eZarra-Nezhad, M., Hasanvand, S., \u0026amp; Akbarzadeh, M. H. (2014). The Shadow Economy and Globalization: A Comparison Between Difference GMM and System GMM Approaches. \u003cem\u003eInternational Journal of Business\u003c/em\u003e, \u003cem\u003e6\u003c/em\u003e, 41\u0026ndash;57. Retrieved from https://api.semanticscholar.org/CorpusID:55272191\u003c/li\u003e\n\u003cli\u003eZhang, J., Zhang, J., \u0026amp; Lee, R. (2001). Mortality decline and long-run economic growth. \u003cem\u003eJournal of Public Economics\u003c/em\u003e, \u003cem\u003e80\u003c/em\u003e(3), 485\u0026ndash;507. https://doi.org/https://doi.org/10.1016/S0047-2727(00)00122-5\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Appendix","content":"\u003cp\u003eHistorical Index of Ethnic Fractionalization (HIEF) Ranking in 1960 and 2013 respectively\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRanking\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCountry\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHIEF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRanking\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCountry\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eHIEF\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLiberia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.887\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLiberia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.889\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTogo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.884\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUganda\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.883\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNigeria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.868\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTogo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSouth Africa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.853\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNepal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMali\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.846\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSouth Africa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.856\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhilippines\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.819\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eChad\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.855\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD.R. of Congo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.816\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eKenya\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.855\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChad\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.805\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMali\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.852\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNepal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.804\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNigeria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSenegal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.803\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGuinea-Bissau\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.808\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEthiopia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.803\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePhilippines\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.807\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBenin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.782\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIndonesia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.803\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGabon\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEast Timor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.802\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYugoslavia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.756\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSierra Leone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.801\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGuinea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.752\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMalawi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.791\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSudan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.745\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCentral African Republic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCote d'Ivoire\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.744\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGabon\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.789\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGhana\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.736\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEthiopia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.783\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCentral African Republic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.733\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAngola\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.779\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBurkina Faso\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBurkina Faso\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.767\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eKuwait\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.765\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndonesia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.709\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBenin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.764\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCongo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAfghanistan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.763\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNiger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.683\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGambia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.762\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCanada\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.682\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNamibia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUSSR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.665\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePakistan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.748\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEcuador\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.665\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSenegal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.747\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eColombia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.657\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSudan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.746\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePeru\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.637\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.743\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTrinidad and Tobago\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.625\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGhana\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.736\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBolivia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.614\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCote d'Ivoire\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.731\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMalaysia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.601\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCanada\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGuatemala\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.598\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGuinea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.727\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMauritania\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMauritania\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.713\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAfghanistan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.586\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eQatar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.708\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePakistan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.585\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eZambia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.706\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBrazil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCongo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.704\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLaos\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.562\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDemocratic Republic of Congo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMexico\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.539\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGuyana\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.695\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBelgium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.515\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUnited Arab Emirates\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.684\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.514\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSpain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.669\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBhutan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.502\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNiger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.666\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePanama\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.497\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEritrea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.659\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCzechoslovakia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.478\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTrinidad and Tobago\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.655\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNicaragua\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.465\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBhutan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.651\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVenezuela\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.457\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDjibouti\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.649\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMorocco\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.453\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eColombia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.639\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCuba\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.451\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBosnia-Herzegovina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.637\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSri Lanka\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.451\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLaos\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.634\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.438\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePeru\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.618\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMyanmar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.433\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePanama\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.612\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDominican Republic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.405\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOman\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.597\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMongolia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBelgium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.592\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThailand\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.387\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTanzania\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.591\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingapore\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.385\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMyanmar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIraq\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.366\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMexico\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.587\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCyprus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.336\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBahrain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.582\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnited Kingdom\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.309\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBolivia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.572\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD.R. of Vietnam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMalaysia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCosta Rica\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMorocco\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.566\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnited States of America\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.259\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMacedonia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.562\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBulgaria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.249\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBrazil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.559\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRomania\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.236\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLatvia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.547\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRepublic of Vietnam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.233\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNicaragua\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.544\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCambodia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eKazakhstan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.538\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSwitzerland\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEcuador\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.528\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIsrael\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFiji\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.528\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUruguay\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.211\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUnited States of America\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.527\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSyria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.199\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTurkey\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.521\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEl Salvador\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.197\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eVenezuela\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSaudi Arabia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.195\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCuba\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.517\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTaiwan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.195\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGuatemala\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.511\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNew Zealand\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.185\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eKyrgyz Republic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.487\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYemen Arab Republic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNew Zealand\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.485\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRwanda\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.164\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMauritius\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.466\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOman\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEstonia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.458\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHonduras\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDominican Republic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.453\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLibya\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIraq\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.446\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTurkey\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCape Verde\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.442\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLebanon\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eChile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.439\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFinland\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMoldova\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.427\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSweden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eZimbabwe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.415\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHaiti\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUnited Kingdom\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.399\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParaguay\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCosta Rica\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.398\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSerbia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.396\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTunisia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBotswana\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.395\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGerman Federal Republic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSingapore\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.395\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAlbania\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSwaziland\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIreland\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRussia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.376\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSomalia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.066\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIsrael\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.376\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eArgentina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.066\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTaiwan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.373\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAustria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAlgeria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.372\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHungary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUkraine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGreece\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSwitzerland\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.367\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eItaly\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGeorgia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.367\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJordan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTajikistan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.367\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGerman Democratic Republic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNetherlands\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.354\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePoland\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eThailand\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.352\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNorway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCyprus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.347\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAustralia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSri Lanka\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.323\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNetherlands\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMongolia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.315\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDenmark\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLesotho\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.313\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJapan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUzbekistan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.313\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMadagascar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBelarus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.309\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEgypt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBurundi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.308\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePortugal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBulgaria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.289\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDemocratic People's Republic of Korea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLithuania\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.284\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRepublic of Korea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRwanda\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAustralia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.276\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDemocratic Republic of Vietnam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.263\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCzech Republic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.262\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLibya\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.259\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSlovenia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.258\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTurkmenistan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.255\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAustria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.248\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSlovakia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.241\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHungary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.232\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHonduras\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.229\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSaudi Arabia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.224\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSomalia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.222\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePortugal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSweden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.219\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSyria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.213\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eJamaica\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRomania\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.207\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMadagascar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.194\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGerman Federal Republic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.189\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eParaguay\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.179\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDenmark\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.177\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUruguay\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.176\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIreland\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.174\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCroatia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.171\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGreece\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.167\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEl Salvador\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.165\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eArgentina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.158\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e137\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCambodia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.158\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNorway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.151\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e139\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAlbania\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.139\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFinland\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.138\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLebanon\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.133\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYemen Arab Republic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.126\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAzerbaijan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.122\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eItaly\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e145\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e 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Income","lastPublishedDoi":"10.21203/rs.3.rs-4115318/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4115318/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAmidst shifting demographics across many countries, certain stylized facts related to fertility, population, and income have become less universally applicable. This research addresses a significant gap in literature by providing a comprehensive analysis on the relationship between population diversity, population growth, and income growth that incorporate both time-varying and cross-country components. Our study reveals a positive correlation between population diversity and population growth, suggesting that diversity along with migration contribute to population expansion due to strategic interactions among ethnic groups to compete for influences in society, hence fostering pronatalism policies. However, we found a negative association between population diversity and income growth, indicating potential ethnic conflict, rent-seeking behaviour, and other challenges that hinder policy implementation in highly diverse settings. Our findings underline the complex dynamics between these factors, emphasizing the need for further exploration.\u003c/p\u003e\n\u003cp\u003eJEL Classification: J1, O1, Z1\u003c/p\u003e","manuscriptTitle":"Analysing the Link between Population Diversity, Population Growth, and Income","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-18 11:42:27","doi":"10.21203/rs.3.rs-4115318/v1","editorialEvents":[{"type":"communityComments","content":1}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"69257408-ffde-48f4-9ae3-b2b77f917a81","owner":[],"postedDate":"March 18th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":29531250,"name":"Other Economics"}],"tags":[],"updatedAt":"2024-03-18T11:42:27+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-18 11:42:27","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4115318","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4115318","identity":"rs-4115318","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}